Staff Data Scientist

Walmart•Sunnyvale, CA

4d•Onsite

About The Position

The Staff Data Scientist develops data sets, statistical analyses, machine-learning systems, algorithms, and custom data models to support innovative business solutions within Walmart eCommerce. The role analyzes large, continuous and offline data flows, identifies trends and relationships, predicts future data characteristics and customer behavior, and develops models to improve search results, product strategies, and business outcomes. The position works with large project teams and cross-functional business partners, translating business needs into data requirements and providing analytical support and subject-matter expertise in statistical analysis and modeling. The role builds and structures data from multiple internal and external sources; develops, trains, validates, scales, and applies algorithms to new and large data sets; evaluates product launches and customer behavior; defines and tracks product KPIs; and researches industry techniques and technologies. Work examples include email targeting, business optimization, and consumer recommendations. The job is located at 1375 Crossman Avenue, Sunnyvale, California.

Requirements

Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or a related field and 2 years of experience in an analytics-related field; OR bachelor’s degree or equivalent in one of these fields and 4 years of experience in an analytics-related field.
Experience using SQL to extract data and perform analysis.
Experience using Python to build machine-learning models and perform complex analysis that cannot be done using SQL.
Experience using Tableau to create dashboards that visually represent key-metric trends.
Experience using A/B testing methodologies to evaluate the impact of new product launches.
Experience using MS Excel for basic calculations and ad hoc analysis.
Experience developing machine-learning models to predict customer behavior and recommend optimized spending strategies.
Experience performing ETL operations to create structured tables from raw, unclean data sources.
Experience using quasi-experimental techniques when A/B tests are not feasible for measuring product launches.
Experience defining KPIs, including activation, retention, churn, and feature adoption.
Experience identifying high-impact cohorts and tailoring product strategies accordingly.
Experience predicting product usage, growth, and the impact of future launches.
Employer will accept any amount of experience with the required skills.

Responsibilities

Build complex data sets from multiple internal and external sources, including structured tables from raw data through ETL operations.
Conduct advanced statistical analysis to identify trends and significant relationships in data.
Build learning systems to analyze and filter continuous data flows and support offline data analysis.
Develop, train, validate, scale, and apply algorithms and models to new and large data sets.
Combine data features to develop search models and provide appropriate search results.
Develop custom data models and algorithms to support business solutions and predict future data characteristics.
Translate business needs into data requirements and collaborate with cross-functional partners and project teams to implement modeling solutions.
Analyze large data sets and provide analytical support and guidance to project teams, including projects involving email targeting, business optimization, and consumer recommendations.
Research industry trends, techniques, best practices, and technologies to support assigned projects.
Serve as a project team's subject-matter expert in statistical analysis and modeling.
Use A/B testing and quasi-experimental techniques to evaluate product launches and their impact.
Define KPIs such as activation, retention, churn, and feature adoption; identify high-impact cohorts and tailor product strategies.
Predict product usage, growth, and the impact of future launches.
Develop models of the current state to determine needed improvements.