Data Scientist Experimentation Analyst 2025PX02001 MCA-003MCAF-40936
Data Scientist Experimentation Analyst 2025PX02001 MCA-003MCAF-40936
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
5years
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
Job Summary
The client is seeking a Data Scientist & Experimentation Analyst to play a critical role in supporting the development and evaluation of MLdriven pricing and personalization solutions. This role provides datadriven insights and rigorous experimentation enabling endtoend support for machine learning initiatives. The ideal candidate will excel in statistical analysis experiment design and data science workflows while supporting ML Scientists in building robust models and analyzing their performance..
Job 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 modelling 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.
AdHoc Analysis: Perform deep dives and provide actionable insights on specific datasets or business questions to 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.
Essential Skills
4 years 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 & machine learning (Pandas NumPy scikitlearn).
Intermediate skills in SQL for data querying including Window Functions Joins and Group By
Familiarity with classical ML techniques like Classification Regression and Clustering using algorithms like XGBoost Random Forest and KMeans.
Experience with data visualization platforms (e.g. Tableau Power BI Matplotlib or Seaborn).
Proficiency in designing and analyzing A/B and multivariate experiments focusing on drawing actionable insights.
Experience working with large complex datasets including preprocessing feature engineering and encoding techniques..
Nice to Haves
Background Check required
No criminal record
Others
Work Timing: Regular Hours Monday to Friday 9am to 5pm
Work Timezone: Global Timezone (GMT 0800) Pacific Time Los Angeles (PST)
Reporting Location: San Jose
Hours per Week: 40
Python machine learning Pandas NumPy sci-kit-learn sql visualization
Employment Type
Full Time
