Data Science Product Analyst

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