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Job Summary

Deloitte is seeking a motivated Power BI Developer to design, develop, and maintain business intelligence dashboards and reporting solutions. The ideal candidate will transform complex data into actionable insights, support business decision-making, and collaborate with cross-functional teams to deliver high-quality analytics solutions.

Job Description

As a Power BI Developer, you will:

• Develop interactive dashboards and reports using Microsoft Power BI.
• Gather and analyze business requirements for reporting solutions.
• Create and optimize data models and relationships.
• Build ETL processes for data extraction and transformation.
• Design KPI dashboards and executive reports.
• Integrate data from databases, APIs, and cloud platforms.
• Ensure data accuracy, security, and governance standards.
• Troubleshoot and optimize report performance.
• Work closely with analysts, developers, and business stakeholders to deliver data-driven solutions.

Key Responsibilities

Dashboard Development

• Build interactive and visually appealing dashboards.
• Create drill-down and drill-through reporting capabilities.
• Develop self-service reporting solutions.

Data Modeling

• Design star and snowflake schema data models.
• Create calculated columns and measures using DAX.
• Develop relationships between multiple datasets.

Data Integration

• Connect Power BI with SQL Server, Excel, SharePoint, and APIs.
• Build automated data refresh pipelines.
• Perform data cleansing and transformation using Power Query.

Reporting & Analytics

• Develop KPIs and performance scorecards.
• Generate business reports and trend analysis.
• Provide actionable insights through data visualization.

Collaboration

• Gather business requirements from stakeholders.
• Translate business needs into technical solutions.
• Present findings and recommendations to management teams.

Required Technical Skills

• Power BI Desktop & Power BI Service
• DAX (Data Analysis Expressions)
• Power Query (M Language)
• SQL & T-SQL
• Microsoft Excel (Advanced)
• Data Modeling & Data Warehousing
• Data Visualization & Dashboard Design
• Basic Python (Preferred)
• Azure Fundamentals (Preferred)
• Strong Communication & Problem-Solving Skills

Preferred Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Science, Business Analytics, or a related field.
• 0–2 years of experience in Power BI, Business Intelligence, or Data Analytics.
• Knowledge of SQL databases and reporting tools.
• Understanding of ETL concepts and data warehousing.
• Microsoft Power BI certification (PL-300) is preferred.

Benefits

✅ Annual Performance Bonus
✅ Medical, Dental, and Vision Insurance
✅ Hybrid Work Environment
✅ Paid Training and Certification Programs
✅ 401(k) Retirement Plan
✅ Career Growth Opportunities

Job Summary

IBM is seeking an Applied Data Scientist specializing in Generative AI to design, develop, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs). The role focuses on transforming business challenges into scalable AI products using machine learning, natural language processing, and Generative AI technologies. IBM's data and analytics teams work on responsible AI adoption and enterprise AI solutions across cloud environments.

Job Description

As an Applied Data Scientist (Generative AI), you will:

• Develop and fine-tune Large Language Models (LLMs) for enterprise applications.
• Build intelligent AI assistants, chatbots, and knowledge management systems.
• Design and implement Retrieval-Augmented Generation (RAG) architectures.
• Create end-to-end machine learning and Generative AI pipelines.
• Work with structured and unstructured data to generate actionable insights.
• Deploy scalable AI solutions on cloud platforms.
• Collaborate with engineering, product, and business teams to deliver AI-driven innovations.
• Evaluate and optimize model performance, accuracy, and reliability.
• Implement responsible AI practices, governance, and model monitoring frameworks. Generative AI, LLMs, and production-grade AI deployment have become core requirements in modern data science roles.

Key Responsibilities

Generative AI Development

• Fine-tune foundation models and LLMs.
• Implement prompt engineering strategies.
• Develop conversational AI and AI agents.

Data Science & Machine Learning

• Build predictive and prescriptive analytics models.
• Perform data preprocessing and feature engineering.
• Conduct experimentation and model evaluation.

Enterprise AI Solutions

• Design RAG systems using vector databases.
• Integrate AI solutions with business applications.
• Develop scalable AI APIs and microservices.

Deployment & MLOps

• Deploy models using Docker and Kubernetes.
• Implement CI/CD pipelines for AI applications.
• Monitor model performance and automate retraining.

Collaboration & Leadership

• Partner with stakeholders to identify AI opportunities.
• Translate business requirements into technical solutions.
• Present findings and recommendations to leadership teams.

Required Technical Skills

• Programming: Python, SQL, PySpark
• Machine Learning: Scikit-learn, XGBoost, TensorFlow, PyTorch
• Generative AI: LLMs, Prompt Engineering, Fine-Tuning, AI Agents
• Frameworks: LangChain, LlamaIndex, Hugging Face
• RAG Systems: Vector Databases, Semantic Search, Embeddings
• Cloud Platforms: AWS, Azure, Google Cloud Platform
• Big Data: Apache Spark, Databricks, Hadoop
• MLOps: MLflow, Docker, Kubernetes, CI/CD
• Databases: PostgreSQL, MongoDB, Pinecone, ChromaDB

Preferred Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Artificial Intelligence, or a related field.
• 3–7+ years of experience in Data Science, Machine Learning, or AI Engineering.
• Hands-on experience with Generative AI applications and LLM deployment.
• Strong understanding of NLP, deep learning, and distributed computing.
• Excellent communication and problem-solving skills.

Benefits

✅ Competitive Salary + Annual Bonus
✅ Stock Options and Performance Incentives
✅ Health, Dental, and Vision Insurance
✅ Hybrid/Remote Work Opportunities
✅ Learning and Certification Programs
✅ Generative AI and Cloud Training

Job Summary

We are seeking a highly skilled Deep Learning Engineer to develop, train, optimize, and deploy state-of-the-art deep learning models for real-world AI applications. The ideal candidate will have expertise in neural networks, computer vision, natural language processing (NLP), generative AI, and large-scale machine learning systems.

You will work with AI researchers, data scientists, software engineers, and product teams to build next-generation AI solutions that power intelligent products and services across industries.

Key Responsibilities

Deep Learning Model Development

• Design, develop, and optimize deep neural network architectures.
• Build and train machine learning and deep learning models using large-scale datasets.
• Develop solutions for Computer Vision, NLP, Speech AI, and Generative AI applications.
• Fine-tune foundation models and Large Language Models (LLMs).

Model Training & Optimization

• Perform hyperparameter tuning and model optimization.
• Improve model accuracy, scalability, and efficiency.
• Implement distributed training strategies for large-scale models.
• Conduct model evaluation and validation.

Production Deployment

• Deploy deep learning models into production environments.
• Develop scalable inference pipelines.
• Monitor model performance and retrain models as required.
• Implement MLOps best practices.

Research & Innovation

• Stay updated on the latest AI research and advancements.
• Experiment with emerging architectures and techniques.
• Collaborate with research teams to translate innovations into production solutions.
• Publish technical findings and contribute to AI knowledge sharing.

Collaboration

• Work closely with data engineering teams to build data pipelines.
• Partner with product teams to define AI requirements.
• Support AI integration across enterprise applications.
• Mentor junior engineers and contribute to technical leadership.

Required Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, or a related field.

Experience

• 3+ years of experience in Deep Learning, Machine Learning, or AI Engineering.
• Experience developing and deploying production-grade AI solutions.
• Strong understanding of neural networks and advanced AI algorithms.

Technical Skills

Programming Languages

• Python
• C++
• SQL

Deep Learning Frameworks

• PyTorch
• TensorFlow
• Keras
• JAX

AI & Machine Learning

• Deep Neural Networks (DNN)
• CNNs (Convolutional Neural Networks)
• RNNs & LSTMs
• Transformers
• Generative AI
• Reinforcement Learning
• Transfer Learning

Specialized Areas

• Computer Vision
• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Multimodal AI
• Speech Recognition

Cloud & Infrastructure

• AWS
• Azure
• Google Cloud Platform (GCP)
• Docker
• Kubernetes

Data & MLOps

• Apache Spark
• MLflow
• Kubeflow
• Airflow
• Git/GitHub

Preferred Certifications

• NVIDIA Deep Learning Institute Certifications
• Google Cloud Professional Machine Learning Engineer
• Microsoft Azure AI Engineer Associate
• Amazon Web Services Machine Learning Specialty

Preferred Skills

• Model Optimization & Quantization
• Distributed Training
• CUDA Programming
• GPU Acceleration
• AI Model Deployment
• MLOps & Model Monitoring
• Research and Innovation
• Problem Solving & Communication Skills

Benefits

• Competitive Base Salary
• Annual Performance Bonus
• RSU/Stock Grants
• Medical, Dental & Vision Insurance
• Flexible Hybrid Work Model
• Learning & Development Programs
• Career Advancement Opportunities

Job Summary

We are seeking a detail-oriented Third-Party Risk Analyst to evaluate, monitor, and manage risks associated with vendors, suppliers, business partners, and external service providers. The ideal candidate will support the organization's Third-Party Risk Management (TPRM) program by conducting risk assessments, ensuring regulatory compliance, and identifying potential cybersecurity, operational, financial, and compliance risks across the vendor ecosystem.

This role collaborates with Procurement, Information Security, Legal, Compliance, Privacy, and Business teams to strengthen vendor governance and minimize organizational risk exposure.

Key Responsibilities

Vendor Risk Assessment

• Conduct comprehensive third-party risk assessments for new and existing vendors.
• Evaluate vendor security controls, compliance posture, and operational resilience.
• Review security questionnaires, SOC reports, audit reports, and risk documentation.
• Perform inherent and residual risk analysis.

Risk Monitoring & Due Diligence

• Monitor vendor risk throughout the vendor lifecycle.
• Identify and assess cybersecurity, operational, legal, privacy, and financial risks.
• Track remediation plans and vendor corrective actions.
• Maintain vendor risk registers and assessment records.

Compliance & Regulatory Support

• Ensure compliance with industry regulations and standards.
• Support audits related to third-party risk management.
• Assist in developing vendor governance policies and procedures.
• Evaluate vendor compliance with contractual security requirements.

Reporting & Stakeholder Management

• Prepare risk assessment reports and executive summaries.
• Present findings and recommendations to management.
• Collaborate with procurement and business units during vendor onboarding.
• Support risk committees and governance meetings.

Continuous Improvement

• Improve third-party risk assessment methodologies.
• Automate vendor risk management processes where possible.
• Monitor emerging risks and industry best practices.
• Contribute to enterprise risk management initiatives.

Required Qualifications

Education

• Bachelor's degree in Cybersecurity, Information Technology, Information Security, Risk Management, Business Administration, or related field.

Experience

• 3+ years of experience in Third-Party Risk Management (TPRM), Vendor Risk Management, Cybersecurity Risk, Compliance, or Information Security.
• Experience reviewing vendor security documentation and audit reports.
• Familiarity with enterprise risk management frameworks.

Technical Skills

• Third-Party Risk Management (TPRM)
• Vendor Risk Assessment
• Cybersecurity Risk Analysis
• Risk Registers & Risk Scoring
• Security Questionnaires
• Vendor Due Diligence
• Contract Risk Review
• Data Privacy Assessments
• Risk Reporting & Governance

Frameworks & Standards

• NIST Cybersecurity Framework
• NIST 800-53
• ISO 27001
• SOC 2
• PCI-DSS
• HIPAA
• GDPR
• CCPA

Tools

• Archer
• OneTrust
• ServiceNow GRC
• LogicGate
• RSA Archer
• Jira
• Microsoft Excel & Power BI

Preferred Certifications

• ISC2 CISSP
• ISACA CISM
• ISACA CRISC
• Shared Assessments Certified Third-Party Risk Professional (CTPRP)
• CompTIA Security+

Preferred Skills

• Strong analytical and risk assessment capabilities.
• Excellent written and verbal communication skills.
• Ability to manage multiple vendor assessments simultaneously.
• Experience working with cross-functional teams.
• Knowledge of cybersecurity controls and cloud security practices.
• Strong stakeholder management and presentation skills.

Job Summary

We are seeking a highly skilled Multimodal AI Engineer to develop next-generation AI systems capable of understanding, processing, and generating content across multiple modalities, including text, images, audio, video, and structured data. The ideal candidate will work on cutting-edge foundation models, vision-language models (VLMs), and multimodal Generative AI applications that power enterprise and consumer experiences.

Job Description

As a Multimodal AI Engineer, you will design, train, fine-tune, and deploy advanced multimodal AI models that integrate computer vision, natural language processing, speech technologies, and generative AI. You will collaborate with research scientists, machine learning engineers, product teams, and cloud architects to build scalable AI solutions for real-world applications.

The role requires expertise in deep learning frameworks, multimodal model architectures, MLOps, cloud computing, and AI model optimization. You will help drive innovation in areas such as AI assistants, intelligent search, content generation, document understanding, video analytics, and autonomous systems.

Key Responsibilities

• Design and develop multimodal AI applications using text, image, audio, and video data.
• Train, fine-tune, and optimize Vision-Language Models (VLMs) and Large Language Models (LLMs).
• Build AI systems that combine natural language understanding with computer vision capabilities.
• Develop Retrieval-Augmented Generation (RAG) pipelines for multimodal content.
• Integrate AI models into enterprise products and cloud platforms.
• Create scalable data pipelines for training and inference workflows.
• Evaluate model performance, accuracy, robustness, and safety.
• Optimize AI models for latency, scalability, and production deployment.
• Collaborate with AI researchers to implement emerging architectures and techniques.
• Ensure responsible AI practices, fairness, security, and compliance standards.
• Monitor production AI systems and continuously improve model performance.
• Stay updated on the latest advancements in Generative AI and multimodal foundation models.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• 4+ years of experience in AI, Machine Learning, Deep Learning, or Data Science.
• Experience building and deploying machine learning models in production environments.
• Strong understanding of multimodal AI systems and foundation models.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.

Required Technical Skills

Artificial Intelligence & Machine Learning

• Deep Learning
• Machine Learning
• Generative AI
• Large Language Models (LLMs)
• Vision-Language Models (VLMs)
• Reinforcement Learning Fundamentals

Computer Vision

• Image Classification
• Object Detection
• Image Captioning
• Visual Question Answering (VQA)
• OCR and Document Intelligence

Natural Language Processing

• NLP
• Transformers
• Prompt Engineering
• Text Generation
• Semantic Search
• RAG Frameworks

Programming & Frameworks

• Python
• PyTorch
• TensorFlow
• Hugging Face Transformers
• OpenCV
• CUDA

Data & MLOps

• MLflow
• Kubeflow
• Docker
• Kubernetes
• Apache Spark
• Airflow

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Preferred Qualifications

• Experience with multimodal foundation models such as GPT-4o, LLaVA, CLIP, Gemini, or similar architectures.
• Knowledge of AI model compression and optimization techniques.
• Experience working with distributed AI training environments.
• Familiarity with vector databases and AI agent frameworks.
• Understanding of Responsible AI and AI governance principles.

Preferred Certifications

• AWS Certified Machine Learning Specialty
• Microsoft Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• NVIDIA Deep Learning Institute Certifications

Tools & Technologies

• Python
• PyTorch
• TensorFlow
• Hugging Face
• LangChain
• LlamaIndex
• OpenCV
• Docker
• Kubernetes
• MLflow
• Databricks
• Snowflake
• Pinecone
• Weaviate
• AWS
• Azure
• GCP

Success Metrics

• Successful deployment of multimodal AI applications.
• Improved model accuracy and user experience.
• Reduced inference latency and operational costs.
• Scalable AI infrastructure and deployment pipelines.
• Increased adoption of AI-powered products and services.
• Compliance with security, privacy, and responsible AI standards.

Job Summary

We are seeking an experienced Zero Trust Security Architect to lead the design, implementation, and optimization of enterprise-wide Zero Trust security strategies. This role is responsible for securing users, devices, applications, workloads, and data across on-premises, cloud, and hybrid environments. The ideal candidate will have deep expertise in security architecture, identity and access management, network segmentation, and cloud security.

Key Responsibilities

• Design and implement enterprise-wide Zero Trust Architecture (ZTA) aligned with business and security objectives.
• Develop security frameworks based on the principle of "Never Trust, Always Verify."
• Architect identity-centric security controls for workforce, partners, and third-party users.
• Lead micro-segmentation initiatives across cloud and on-premises environments.
• Implement continuous authentication and authorization mechanisms.
• Design secure access solutions for remote and hybrid workforces.
• Evaluate existing security infrastructure and recommend Zero Trust transformation strategies.
• Collaborate with Security Operations, Cloud, Network, and Infrastructure teams.
• Develop security reference architectures, standards, and best practices.
• Conduct security risk assessments and architecture reviews.
• Ensure compliance with NIST, CISA, ISO 27001, SOC 2, and other security frameworks.
• Support incident response and threat mitigation initiatives.
• Present architectural recommendations to executive leadership and stakeholders.

Required Qualifications

• Bachelor's degree in Cybersecurity, Information Technology, Computer Science, or a related field.
• 8+ years of experience in Cybersecurity, Security Engineering, or Security Architecture.
• 3+ years of experience designing or implementing Zero Trust security models.
• Strong understanding of enterprise security architecture principles.
• Experience securing cloud, hybrid, and multi-cloud environments.
• Excellent communication, leadership, and stakeholder management skills.

Required Technical Skills

Zero Trust & Security Architecture

• Zero Trust Architecture (ZTA)
• Security Architecture Design
• Enterprise Security Frameworks
• Security Risk Management
• Security Controls Assessment

Identity & Access Management (IAM)

• Single Sign-On (SSO)
• Multi-Factor Authentication (MFA)
• Privileged Access Management (PAM)
• Identity Governance & Administration (IGA)
• Conditional Access Policies

Cloud Security

• AWS Security
• Microsoft Azure Security
• Google Cloud Security
• Cloud Access Security Broker (CASB)
• Secure Access Service Edge (SASE)

Network Security

• Micro-Segmentation
• Software-Defined Perimeter (SDP)
• Secure Remote Access
• Network Access Control (NAC)
• Firewall Architecture

Security Operations

• SIEM Solutions
• Endpoint Detection & Response (EDR)
• Extended Detection & Response (XDR)
• Security Monitoring
• Threat Intelligence

Preferred Certifications

• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)
• Certified Information Security Manager (CISM)
• GIAC Security Certifications (GIAC)
• Microsoft Cybersecurity Architect Expert
• AWS Security Specialty
• Zero Trust Professional Certifications

Tools & Technologies

• Microsoft Entra ID (Azure AD)
• Okta
• CyberArk
• Palo Alto Networks
• Zscaler
• CrowdStrike
• Microsoft Defender
• Splunk
• AWS
• Azure
• Google Cloud Platform (GCP)
• Terraform
• Kubernetes

Success Metrics

• Successful implementation of Zero Trust initiatives.
• Reduction in unauthorized access risks.
• Improved identity and access governance.
• Enhanced cloud and network security posture.
• Compliance audit readiness and reduced security gaps.
• Faster detection and response to cyber threats.

Benefits

• Competitive Base Salary
• Annual Performance Bonus
• Health, Dental, and Vision Insurance
• Remote/Hybrid Work Flexibility
• Paid Time Off (PTO)
• Professional Certifications & Training Reimbursement
• Employee Wellness Programs
• Leadership Development Opportunities

Job Summary

We are seeking a highly analytical and business-oriented Data Science Product Analyst to transform data into actionable insights that drive product growth, customer engagement, and business performance. The ideal candidate will work closely with Product Managers, Data Scientists, Engineers, and Business Leaders to evaluate product performance, conduct experiments, and recommend data-driven improvements.

Key Responsibilities

• Analyze user behavior and product performance using large-scale datasets.
• Design, execute, and evaluate A/B tests and product experiments.
• Develop dashboards, reports, and KPI tracking frameworks.
• Identify growth opportunities through data exploration and predictive analytics.
• Collaborate with Product Managers to define product success metrics.
• Generate actionable insights to improve customer acquisition, retention, and engagement.
• Build statistical models to forecast product performance and user behavior.
• Monitor key business metrics and identify trends, anomalies, and opportunities.
• Present findings and recommendations to stakeholders and executive leadership.
• Support product roadmap decisions with data-driven analysis.

Required Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• 3+ years of experience in Product Analytics, Data Science, Business Analytics, or a related role.
• Strong proficiency in SQL for data extraction and analysis.
• Experience with Python or R for statistical analysis and modeling.
• Knowledge of experimentation methodologies and A/B testing.
• Strong analytical, problem-solving, and communication skills.
• Experience working with large datasets and cloud-based analytics platforms.

Preferred Skills

• Product Analytics
• Statistical Modeling
• A/B Testing & Experimentation
• SQL
• Python (Pandas, NumPy, Scikit-learn)
• Tableau, Power BI, or Looker
• Data Visualization
• Customer Journey Analytics
• Predictive Analytics
• Machine Learning Fundamentals
• Google Analytics or Adobe Analytics
• Data Warehousing (Snowflake, BigQuery, Redshift)

Tools & Technologies

• SQL
• Python / R
• Tableau
• Power BI
• Looker
• Snowflake
• Google BigQuery
• AWS / Azure / GCP
• Jupyter Notebook
• Excel

Success Metrics

• Improved product adoption and user engagement.
• Increased customer retention and conversion rates.
• Accurate forecasting and business insights.
• Effective experimentation and data-driven product decisions.
• Enhanced reporting and KPI visibility across teams.

Benefits

• Competitive Salary
• Annual Performance Bonus
• Health, Dental, and Vision Insurance
• Remote/Hybrid Work Flexibility
• Paid Time Off (PTO)
• Professional Development & Certifications
• Career Growth Opportunities
• Employee Wellness Programs

Job Description

We are seeking a detail-oriented AI Evaluation Specialist to evaluate, benchmark, and improve the performance of cutting-edge Artificial Intelligence systems, including Large Language Models (LLMs), Generative AI applications, AI agents, and multimodal models. This emerging role sits at the intersection of AI Quality Assurance, Data Analytics, Prompt Engineering, and Responsible AI. The ideal candidate will help ensure AI systems deliver accurate, safe, unbiased, and high-quality outputs while supporting continuous model improvement.

Key Responsibilities

• Evaluate AI-generated content for accuracy, relevance, coherence, safety, and factual correctness.
• Develop evaluation frameworks, scoring rubrics, and benchmark datasets for AI model assessment.
• Conduct prompt testing and adversarial testing to identify weaknesses and edge cases.
• Analyze model outputs to detect hallucinations, bias, toxicity, and performance gaps.
• Collaborate with AI Engineers and Data Scientists to improve model quality and user experience.
• Perform Human-in-the-Loop (HITL) reviews and provide structured feedback for model refinement.
• Design and execute A/B testing experiments for AI applications.
• Monitor production AI systems and track key performance metrics.
• Review training datasets and identify data quality issues.
• Support Responsible AI, AI Governance, and compliance initiatives.
• Create reports and recommendations for leadership and product teams.
• Stay current with emerging trends in Generative AI, Agentic AI, and AI evaluation methodologies.

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Linguistics, Mathematics, Psychology, or a related field.
• 1–3 years of experience in AI evaluation, data annotation, quality assurance, machine learning operations, or content analysis.
• Strong analytical and critical-thinking skills.
• Excellent written communication and documentation abilities.
• Understanding of Generative AI, Machine Learning, and Large Language Models.
• Experience working with structured evaluation processes and quality standards.

Preferred Qualifications

• Experience with Prompt Engineering and LLM optimization.
• Familiarity with AI Safety, Responsible AI, and model governance practices.
• Knowledge of Python, SQL, and data visualization tools.
• Experience with AI benchmarking platforms and evaluation metrics.
• Exposure to Retrieval-Augmented Generation (RAG) systems and AI agents.
• Experience evaluating multilingual AI systems.

Technical Skills

• AI Model Evaluation
• Large Language Models (LLMs)
• Prompt Engineering
• Generative AI Testing
• AI Benchmarking
• Human-in-the-Loop (HITL) Evaluation
• Python
• SQL
• Data Analytics
• AI Safety & Governance
• Machine Learning Fundamentals
• Quality Assurance (QA)

Key Competencies

• Critical Thinking
• Attention to Detail
• Problem Solving
• Research & Analysis
• Communication Skills
• Decision Making
• Collaboration
• Ethical AI Awareness

Job Description

A Management Consultant helps organizations improve business performance, solve operational challenges, optimize processes, and develop growth strategies. The consultant works closely with executives and stakeholders to analyze business problems, identify opportunities, and implement solutions that drive efficiency, profitability, and long-term success.

Key Responsibilities

• Analyze business operations, processes, and organizational structures to identify improvement opportunities.
• Conduct market research, competitive analysis, and industry benchmarking.
• Develop strategic recommendations to improve efficiency, productivity, and profitability.
• Lead business transformation and change management initiatives.
• Assess organizational performance and recommend process improvements.
• Facilitate stakeholder meetings, workshops, and executive presentations.
• Create business cases, financial models, and implementation roadmaps.
• Support mergers, acquisitions, restructuring, and organizational development projects.
• Monitor project performance and ensure successful delivery of consulting engagements.
• Collaborate with cross-functional teams to implement strategic initiatives.
• Prepare detailed reports, dashboards, and executive-level presentations.
• Advise senior leadership on operational, financial, and strategic decisions.

Required Qualifications

• Bachelor's degree in Business Administration, Management, Finance, Economics, or a related field.
• 3+ years of experience in consulting, business analysis, project management, or corporate strategy.
• Strong analytical, problem-solving, and decision-making skills.
• Experience with data analysis and business performance metrics.
• Excellent communication, presentation, and stakeholder management abilities.
• Ability to manage multiple projects in a fast-paced environment.

Preferred Qualifications

• MBA or Master's degree in Business, Strategy, or Management.
• Experience with business transformation or digital transformation initiatives.
• Knowledge of Lean, Six Sigma, Agile, or Project Management methodologies.
• Consulting experience with Fortune 500 companies is preferred.

Technical Skills

• Strategic Planning
• Business Process Improvement
• Financial Analysis
• Data Analytics
• Market Research
• Change Management
• Risk Assessment
• Project Management
• Microsoft Excel
• Power BI / Tableau
• Business Intelligence Tools
• Stakeholder Management

Key Competencies

• Strategic Thinking
• Leadership
• Problem Solving
• Communication
• Negotiation
• Business Acumen
• Client Relationship Management
• Decision Making
• Adaptability

Job Description

A Wireless Network Engineer is responsible for designing, implementing, maintaining, and optimizing wireless network infrastructure to ensure reliable, secure, and high-performance connectivity across enterprise environments. This role focuses on Wi-Fi technologies, RF engineering, network security, troubleshooting, and wireless network scalability.

Key Responsibilities

• Design, deploy, and manage enterprise wireless networks and Wi-Fi infrastructure.
• Configure and maintain wireless access points (APs), controllers, and cloud-managed wireless solutions.
• Conduct RF site surveys and wireless coverage assessments.
• Optimize wireless network performance, capacity, and roaming capabilities.
• Monitor network health and troubleshoot connectivity, latency, and interference issues.
• Implement wireless security solutions, including WPA3, 802.1X authentication, and network access control (NAC).
• Collaborate with network, security, and infrastructure teams to support business requirements.
• Analyze wireless network traffic and identify performance bottlenecks.
• Support Wi-Fi 6, Wi-Fi 6E, and Wi-Fi 7 deployments.
• Create and maintain network diagrams, documentation, and technical reports.
• Ensure compliance with organizational security policies and industry standards.
• Provide technical support for wireless network incidents and escalations.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Network Engineering, or a related field.
• 3+ years of experience in wireless networking and infrastructure support.
• Strong understanding of IEEE 802.11 wireless standards.
• Knowledge of TCP/IP, DNS, DHCP, VLANs, VPNs, and routing protocols.
• Experience with wireless controllers and cloud-managed wireless solutions.
• Familiarity with RF spectrum analysis and wireless troubleshooting tools.

Preferred Certifications

• Cisco CCNA Enterprise
• Cisco CCNP Enterprise
• CWNA (Certified Wireless Network Administrator)
• CWNP (Certified Wireless Network Professional)
• Aruba Certified Mobility Associate (ACMA)

Technical Skills

• Wireless LAN (WLAN) Design
• RF Planning and Site Surveys
• Cisco Wireless Solutions
• Aruba Wireless Solutions
• Meraki Wireless Management
• Wi-Fi Security and Authentication
• Network Monitoring and Troubleshooting
• Spectrum Analysis Tools
• Network Automation Basics
• Wi-Fi 6/6E and Wi-Fi 7 Technologies

Job Description

We are seeking an experienced and innovative AI Product Manager to lead the strategy, development, and launch of AI-powered products and solutions. The ideal candidate will bridge the gap between business objectives, customer needs, data science teams, and engineering organizations to deliver impactful AI-driven experiences.

As an AI Product Manager, you will define product vision, prioritize features, manage product roadmaps, and ensure successful implementation of machine learning and generative AI technologies. You will work closely with AI engineers, data scientists, UX designers, and business stakeholders to build scalable and responsible AI solutions.

Key Responsibilities

• Define and execute product strategy for AI and machine learning initiatives.
• Develop and maintain product roadmaps aligned with business goals.
• Collaborate with AI engineers, data scientists, and software development teams to deliver AI-powered products.
• Gather and prioritize product requirements from customers, stakeholders, and market research.
• Identify opportunities to leverage Generative AI, Machine Learning, NLP, and predictive analytics.
• Lead the product lifecycle from concept, development, testing, launch, and optimization.
• Monitor product performance and key business metrics.
• Conduct competitive analysis and market research on AI trends.
• Work with legal, compliance, and security teams to ensure responsible AI practices.
• Communicate product vision and progress to executive leadership and stakeholders.
• Define success metrics and measure product impact.
• Support go-to-market strategies and product adoption initiatives.

Required Qualifications

• Bachelor's degree in Computer Science, Business Administration, Engineering, Data Science, or related field.
• 3+ years of Product Management experience.
• Experience working with AI, Machine Learning, Data Analytics, or Software products.
• Strong understanding of product development methodologies.
• Excellent communication, leadership, and stakeholder management skills.
• Ability to translate technical concepts into business value.

Preferred Qualifications

• Master's degree in Business Administration (MBA), Data Science, Artificial Intelligence, or related field.
• Experience with Generative AI, LLMs, and AI-powered applications.
• Knowledge of Agile, Scrum, and Product Lifecycle Management.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with data analytics tools and SQL.

Technical Skills

• Product Strategy & Roadmapping
• Artificial Intelligence
• Machine Learning
• Generative AI
• Large Language Models (LLMs)
• Agile & Scrum Methodologies
• Market Research
• Product Analytics
• SQL
• Data Visualization
• Cloud Platforms (AWS, Azure, GCP)
• Stakeholder Management
• Business Analysis

Benefits

• Competitive Salary
• Annual Performance Bonus
• Stock Options / RSUs
• Medical, Dental, and Vision Insurance
• Remote & Hybrid Work Options
• Professional Development Programs
• Employee Wellness Benefits
• Career Growth Opportunities

Job Description

We are seeking a highly motivated Blue Team Security Engineer to join our Cyber Defense team. The successful candidate will be responsible for protecting enterprise systems, networks, cloud environments, and digital assets from cyber threats. This role focuses on threat detection, incident response, security monitoring, and continuous improvement of defensive security capabilities.

The ideal candidate has experience with Security Operations Center (SOC) processes, threat hunting, incident response, security monitoring technologies, and vulnerability management. You will work closely with security analysts, incident responders, and IT teams to strengthen the organization's security posture and defend against evolving cyber threats.

Key Responsibilities

• Monitor and analyze security events using SIEM and endpoint detection platforms.
• Investigate suspicious activities, security alerts, and potential cyber incidents.
• Conduct proactive threat hunting to identify hidden threats and malicious activity.
• Develop and maintain threat detection rules and security use cases.
• Respond to cybersecurity incidents and coordinate containment, eradication, and recovery efforts.
• Analyze malware, phishing attacks, ransomware activity, and other cyber threats.
• Collaborate with Red Team members to improve security controls and detection capabilities.
• Perform vulnerability assessments and support remediation activities.
• Implement security best practices across network, cloud, and endpoint environments.
• Create incident reports and communicate findings to stakeholders.
• Assist in developing security playbooks, procedures, and response plans.
• Support compliance initiatives and security audits.
• Stay current with emerging cyber threats, attack techniques, and industry trends.

Required Qualifications

• Bachelor's degree in Cybersecurity, Information Security, Computer Science, or a related field.
• 3+ years of experience in cybersecurity operations, incident response, or security engineering.
• Experience with SIEM platforms such as Splunk, Microsoft Sentinel, QRadar, or Elastic.
• Knowledge of network security principles, firewalls, IDS/IPS, and endpoint protection technologies.
• Understanding of cyber threat intelligence and MITRE ATT&CK Framework.
• Experience with Windows, Linux, and cloud security environments.
• Strong analytical and problem-solving skills.
• Excellent communication and documentation abilities.

Preferred Qualifications

• Security certifications such as Security+, CySA+, GCIH, GCIA, CISSP, or CEH.
• Experience with EDR/XDR platforms such as CrowdStrike Falcon, Microsoft Defender, or SentinelOne.
• Knowledge of scripting languages including Python, PowerShell, or Bash.
• Familiarity with malware analysis and digital forensics.
• Experience in cloud platforms such as AWS, Azure, or Google Cloud.

Technical Skills

• Security Monitoring
• Threat Hunting
• Incident Response
• Vulnerability Management
• SIEM Administration
• Endpoint Detection & Response (EDR)
• Network Security
• Threat Intelligence
• Windows & Linux Security
• Cloud Security
• Python
• PowerShell
• MITRE ATT&CK
• Digital Forensics

Benefits

• Competitive Salary
• Annual Performance Bonus
• Health, Dental, and Vision Insurance
• Remote/Hybrid Work Flexibility
• Professional Certification Reimbursement
• Employee Wellness Programs
• Career Development Opportunities

Job Description

We are seeking a detail-oriented and analytical Healthcare Data Analyst to support data-driven decision-making within healthcare operations. The Healthcare Data Analyst will collect, analyze, interpret, and report healthcare data to improve patient outcomes, optimize operational efficiency, ensure regulatory compliance, and support strategic initiatives. The ideal candidate will possess strong analytical skills, experience with healthcare datasets, and the ability to translate complex data into actionable insights for clinical and business stakeholders.

Key Responsibilities

• Collect, clean, validate, and analyze healthcare data from multiple sources.
• Develop and maintain dashboards, reports, and data visualizations to monitor healthcare performance.
• Analyze patient care, clinical, financial, and operational data to identify trends and opportunities for improvement.
• Support quality improvement initiatives by measuring key healthcare performance indicators.
• Monitor healthcare metrics such as patient outcomes, readmission rates, length of stay, and patient satisfaction scores.
• Collaborate with physicians, nurses, administrators, and leadership teams to provide actionable insights.
• Prepare reports for regulatory compliance and accreditation requirements.
• Conduct statistical analyses to evaluate healthcare programs and initiatives.
• Identify data discrepancies and implement solutions to improve data quality.
• Support population health management and value-based care initiatives.
• Assist in forecasting, budgeting, and resource planning through data analysis.
• Present findings and recommendations to management and stakeholders.
• Ensure compliance with healthcare data privacy and security regulations.
• Maintain documentation of data processes, methodologies, and reporting standards.

Required Qualifications

• Bachelor's degree in Health Informatics, Healthcare Administration, Data Analytics, Statistics, Public Health, Computer Science, or a related field.
• 2+ years of experience in healthcare analytics, business analytics, or data analysis.
• Strong proficiency in SQL for data extraction and analysis.
• Advanced knowledge of Microsoft Excel.
• Experience with data visualization tools such as Tableau, Power BI, or Looker.
• Understanding of healthcare databases, Electronic Health Records (EHR), and healthcare reporting systems.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently and manage multiple projects.

Preferred Qualifications

• Master's degree in Health Informatics, Data Science, or a related field.
• Experience with healthcare analytics platforms.
• Knowledge of predictive analytics and machine learning techniques.
• Familiarity with healthcare regulations including HIPAA.
• Experience with Python, R, or SAS for advanced analytics.

Technical Skills

• SQL
• Microsoft Excel
• Power BI
• Tableau
• Python
• R Programming
• Healthcare Data Analytics
• Data Visualization
• Statistical Analysis
• Data Modeling
• Healthcare Reporting
• Database Management

Key Performance Indicators (KPIs)

• Patient Readmission Rate Analysis
• Patient Satisfaction Metrics
• Clinical Quality Measures
• Healthcare Cost Reduction Initiatives
• Data Accuracy and Integrity
• Operational Efficiency Improvements
• Regulatory Compliance Reporting
• Population Health Outcomes

Benefits

• Competitive Salary
• Health, Dental, and Vision Insurance
• Paid Time Off (PTO)
• Remote/Hybrid Work Options
• Professional Development Programs
• Tuition Assistance
• Employee Wellness Programs

Job Summary

We are seeking an ESG Data Analyst to support Environmental, Social, and Governance (ESG) reporting, sustainability initiatives, and regulatory compliance programs. The successful candidate will collect, analyze, validate, and interpret ESG-related data to help organizations meet sustainability goals, improve transparency, and comply with evolving ESG reporting requirements.

Job Description

The ESG Data Analyst will work closely with Sustainability, Risk, Compliance, Finance, and Corporate Governance teams to manage ESG datasets, develop performance metrics, prepare sustainability reports, and support ESG audits. This role is ideal for professionals interested in combining data analytics, sustainability, corporate responsibility, and regulatory compliance.

Key Responsibilities

• Collect, validate, and analyze ESG-related data from multiple business units.
• Develop ESG performance dashboards and reporting metrics.
• Monitor Environmental, Social, and Governance KPIs.
• Support sustainability reporting initiatives and disclosures.
• Conduct ESG risk assessments and trend analysis.
• Assist in carbon emissions and climate-related reporting.
• Prepare ESG reports for internal and external stakeholders.
• Ensure data quality, accuracy, and compliance with reporting standards.
• Collaborate with Sustainability, Compliance, and Risk Management teams.
• Support ESG audits and regulatory reporting requirements.
• Analyze diversity, equity, and inclusion (DEI) metrics.
• Monitor evolving ESG regulations and reporting frameworks.

Environmental Responsibilities

• Track greenhouse gas (GHG) emissions data.
• Analyze energy consumption and sustainability metrics.
• Support carbon footprint reduction initiatives.
• Monitor environmental compliance indicators.

Social Responsibilities

• Analyze workforce diversity and inclusion data.
• Measure employee engagement metrics.
• Monitor community impact initiatives.
• Track workplace health and safety performance.

Governance Responsibilities

• Support governance reporting and compliance efforts.
• Analyze board diversity and governance metrics.
• Monitor ethical and regulatory compliance indicators.
• Assist with governance risk assessments.

Required Qualifications

• Bachelor's degree in Data Analytics, Environmental Science, Sustainability, Business Analytics, Finance, Economics, or related field.
• 2+ years of experience in Data Analytics, ESG Reporting, Sustainability, Risk, or Compliance.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication abilities.

Preferred Qualifications

• Experience with ESG reporting frameworks.
• Knowledge of sustainability regulations and reporting standards.
• Experience in corporate sustainability programs.
• Familiarity with climate risk reporting requirements.

Technical Skills

• SQL
• Excel (Advanced)
• Power BI
• Tableau
• Python
• Data Visualization
• ESG Reporting Tools
• Data Quality Management
• Statistical Analysis
• Sustainability Analytics

ESG Framework Knowledge

• Global Reporting Initiative (GRI)
• Sustainability Accounting Standards Board (SASB)
• Task Force on Climate-related Financial Disclosures (TCFD)
• International Sustainability Standards Board (ISSB)

Preferred Certifications

• Certificate in ESG Investing
• Sustainability and Climate Risk (SCR) Certificate
• GRI Certified Sustainability Professional
• Certified ESG Analyst (CESGA)