Product Data Scientist - W2 Contract (Domain: Product Analytics, Payments, Commerce/E-Commerce)

Job Details
Product Data Scientist
Long Term Contract
Cupertino, CA (Hybrid 3 Days Onsite)

Domain: Product Analytics, Payments, Commerce/E-Commerce
Role Type: Hands-on Data Science and Product Analytics

Key Responsibilities:
· Perform exploratory data analysis (EDA) and ad-hoc analysis to identify trends, opportunities, and areas for product improvement.
· Define and track key product performance metrics (KPIs), including product adoption, customer retention, conversion rates, and transaction success rates.
· Design, execute, and evaluate A/B tests and experiments to measure the impact of product features and business initiatives.
· Develop predictive models and machine learning solutions to improve customer experience and business performance.
· Analyze product launches, measure their impact, and recommend optimization opportunities.
· Translate complex data into actionable insights and present recommendations to Product, Business, Engineering, and leadership teams.
· Work closely with cross-functional teams to understand business requirements and develop data-driven solutions.
· Build and maintain data science pipelines and analytical solutions.
· Explore AI and Generative AI use cases to improve product capabilities and business outcomes.
· Support data quality, governance, and responsible data usage.

Tools, Technologies & Required Skills:
Programming & Data Platforms
· Strong hands-on experience with Python and SQL.
· Experience with relational databases and large-scale data platforms.
· Experience developing data pipelines and processing large datasets.

Machine Learning & Predictive Analytics
· Hands-on experience with classification, regression, clustering, and anomaly detection.
· Experience developing, evaluating, and optimizing machine learning models.
· Knowledge of predictive modeling, feature engineering, and model performance evaluation.
· Familiarity with ML libraries such as scikit-learn, XGBoost, or equivalent tools.

Statistical Analysis & Experimentation
· Strong understanding of statistical analysis and hypothesis testing.
· Practical experience designing and evaluating A/B tests.
· Experience defining product KPIs and measuring product performance.
· Ability to interpret experiment results and recommend improvements.

Business Intelligence & Visualization
· Experience with Tableau or similar BI and visualization tools.
· Ability to build dashboards, analyze trends, and communicate insights.

Additional / Preferred Skills
· Experience in payments, commerce, e-commerce, or customer-facing digital products.
· Exposure to AI / Generative AI solutions and business use cases.
· Experience working with Product, Engineering, Business, and Data teams.
· Strong communication skills and experience presenting findings to senior stakeholders.

Important: We are looking for a hands-on Product Data Scientist, not someone whose experience is limited to data engineering or machine learning model development. Candidates should demonstrate practical experience in product analytics, A/B experimentation, KPI measurement, and translating analytical findings into business decisions