Data Scientist/ML & Experimentation Specialist

• Location: San Jose, CA 95002 (Onsite)
• Visa: USC & GC only
• Duration: 9 Months
• Interview Mode: Video

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Job Summary:

Client is seeking a Data Scientist & Experimentation Analyst to play a critical role in developing and evaluating ML-driven pricing and personalization solutions. The role involves providing data-driven insights and rigorous experimentation to support machine learning initiatives. The ideal candidate will have expertise in statistical analysis, experiment design, and data science workflows while collaborating closely with ML Scientists to build robust models and analyze performance.

Looking for a “STUD” Candidate:

• Someone technically strong in ML, data science, and experimentation
• A candidate who can own A/B testing and experimentation frameworks
• A problem-solver who works with engineers, scientists, and product teams
• Someone data-driven, analytical, and impact-focused

Qualifications:

• 4+ years of experience in data science, experimentation analysis, or a related role supporting ML projects and experimentation.
• Strong understanding of statistical methods, experiment design, and causal inference techniques.
• Proficiency in Python for data manipulation and machine learning (Pandas, NumPy, sci-kit-learn).
• Intermediate proficiency in SQL, including Window Functions, Joins, and Group By queries.
• Familiarity with classical ML techniques such as Classification, Regression, and Clustering using algorithms like XGBoost, Random Forest, and KMeans.
• Experience with data visualization platforms (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Expertise in designing and analyzing A/B and multivariate experiments with a focus on actionable insights.
• Experience working with large, complex datasets, including preprocessing, feature engineering, and encoding techniques.

Key Responsibilities:

• Experiment Design & Analysis: Design, execute, and interpret controlled experiments (e.g., A/B tests, multivariate tests) to evaluate the effectiveness of ML models and strategies.
• Data Analysis & Insights: Conduct exploratory data analysis (EDA), hypothesis testing, and statistical modeling to support ML and business objectives.
• ML Model Support: Assist ML Scientists in preparing data, engineering features, and evaluating models for pricing and personalization solutions.
• Reporting & Visualization: Create dashboards and visualizations to track key metrics, experiment outcomes, and model performance.
• Ad-Hoc Analysis: Perform deep dives on specific datasets or business questions to provide actionable insights and inform strategic decisions.
• Collaboration: Partner with ML Scientists, Data Engineers, and Product Managers to align on experimentation goals and ensure successful implementation of ML solutions.

Preferred Skills:

• Experience in cloud-based data science platforms (AWS, GCP, or Azure).
• Familiarity with business intelligence tools and experimentation platforms.
• Strong problem-solving and analytical thinking skills.
• Excellent communication and collaboration abilities.