Staff Data Scientist

Walmart

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Quick summary

Work type: On-site
Location: Sunnyvale, CA
Employment: Full-time
Posted: 106 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $188k

$119k $236k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $162,000–$214,500.

Based on 240 similar postings.

Employer

About Walmart

Walmart Inc. is the world''s largest retailer by revenue, operating a chain of hypermarkets, discount department stores, and grocery stores, as well as a growing e-commerce presence through Walmart.com. Industry: General Merchandise & Grocery Retail

Walmart currently has 825 open roles on FindRole.

Listed pay typically runs $121,000–$242,000 across 473 roles with salary data.

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At a glance

TL;DR · Staff Data Scientist

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As a Staff Data Scientist on the Spark Driver Platform team, you will lead a team of Applied Scientists to develop machine learning and reinforcement learning models for driver search and matching. You will design, train, evaluate, deploy, and monitor production models while collaborating with business, product, and engineering stakeholders to align AI objectives with strategic goals. Your daily work involves building end-to-end models, optimizing pipelines for real-time processing, and researching state-of-the-art techniques. You will utilize Python, Java, C, C++, Spark, Hive, and cloud platforms like GCP or Azure. The role focuses on solving complex problems in capacity planning, driver offer pricing, surge pricing, incentive strategy, ETA prediction, and trust safety to improve operational efficiency and delivery reliability within a large-scale local delivery service.

What does a Data Scientist earn in California?

Median $214500 from 114 postings across 26 companies.

See salary data

Skills

Machine Learning Reinforcement Learning Deep Learning LLM GenAI Python Java C C++ Spark Hive GCP Azure scikit learn TensorFlow Scala R

What you'll do

Lead a team of applied scientists in developing innovative AI-driven solutions.
Research and implement state-of-the-art machine learning techniques including reinforcement learning and deep learning.
Design and optimize machine learning pipelines for scalability, efficiency, and real-time processing.
Build and deploy end-to-end models that balance accuracy with computational efficiency and business impact.
Monitor production models to ensure they meet performance standards and business goals.
Integrate the latest advancements in AI to improve driver search, matching, and pricing strategies.

What we're looking for

Ph.D. or equivalent advanced degree in Computer Science, Statistics, Operations Research, Economics, or a related field.
Bachelor's degree in a related field with 4 years of analytics experience, a Master's with 2 years, or 6 years of experience.
Extensive experience in machine learning, reinforcement learning, GenAI, and LLMs.
5+ years of experience deploying ML models in production, preferably in high-scale environments (preferred).
Strong programming skills in Python, Java, C, or C++.
Experience with large-scale data systems (Spark/Hive) and cloud computing (GCP/Azure).
Demonstrated ability to lead teams and drive projects from conception to production in a fast-paced environment.
Successful completion of assessments in Python, Spark, Scala, or R (preferred).

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