Senior Data Scientist
Walmart

Job Info

What you'll do at

What you'll do...

Position: Senior Data Scientist

Job Location: 680 W. California Avenue, Sunnyvale, CA 94086

Duties: Develop and implement advanced machine learning models to resolve consumer fraud in Walmart eCommerce applications. Build and automate scalable data pipelines to ingest data from multiple data sources, including structured and unstructured big data. Implement and evaluate predictive modeling solutions using ensemble techniques including but not limited to XGBoost, Gradient boosting models, and Random Forest. Implement unsupervised learning techniques for risk segmentation to improve overall fraud detection capabilities (Clustering Techniques, Self-Organizing Map Neural Networks, K-means, DBScan, and Hierarchical clustering methodologies). Build automated Machine Learning operations to produce repeatable and governable machine learning artifacts. Implement continually learning systems with instant feedback loop to capture fast-moving fraudulent patterns. Research and experiment with the latest state-of-the-art technologies in Data Science, Machine learning, and Deep Learning.

Minimum education and experience required: Master's degree or equivalent in Statistics, Economics, Finance, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 year of experience in an analytics related field; OR Bachelor's degree or equivalent in Statistics, Economics, Finance, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years of experience in an analytics related field.

Skills required: Experience coding in programming languages including Python and Javascript. Experience with database management systems and relational database query languages. Experience with data mining, machine learning, and statistical analysis. Experience working with large data sets and distributed computing. Experience building dashboards. Experience working with cross functional teams. Experience supporting data driven business decisions. Experience designing, building, and deploying real time models using statistical and machine learning algorithms. Employer will accept any amount of experience with the required skills.

Salary Range: $170,186/year to $234,000/year. Additional compensation includes annual or quarterly performance incentives. Additional compensation for certain positions may also include: Regional Pay Zone (RPZ) (based on location) and Stock equity incentives.

Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.

Wal-Mart is an Equal Opportunity Employer.

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About Walmart

At Walmart, we help people save money so they can live better. This mission serves as the foundation for every decision we make, from responsible sourcing to sustainability-and everything in between. As a Walmart associate, you will play an integral role in shaping the future of retail, tech, merchandising, finance and hundreds of other industries-all while affecting the lives of millions of customers all over the world. Here, your work makes an impact every day. What are you waiting for?

Walmart, Inc. is an Equal Opportunity Employer- By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, abilities, ideas and opinions- while being inclusive of all people.

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