Senior Data Scientist

Walmart

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Quick summary

Work type: On-site
Location: Hoboken, NJ
Employment: Full-time
Posted: 1 day ago
Freshness: Confirmed live today
Closes: Nov 11, 2026
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $157k

$99k $214k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$186,250.

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 939 open roles on FindRole.

Listed pay typically runs $117,000–$220,000 across 538 roles with salary data.

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At a glance

TL;DR · Senior Data Scientist

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JOB TITLE: Senior Data Scientist The Senior Data Scientist will join a team to develop and implement advanced data science and artificial intelligence solutions to support business decision-making. The role involves building, analyzing, and interpreting statistical, machine learning, and predictive models for large-scale datasets. Key responsibilities include designing analytical approaches to evaluate business performance, quantifying marketing investments through Marketing Mix Models, and performing regression modeling and time-series analysis. The candidate will use Python, including Pandas, NumPy, and Scikit-learn, alongside SQL for data extraction and transformation. Core tasks involve exploratory data analysis, feature engineering, and causal inference using Difference-in-Differences techniques. This position solves complex business problems by translating data into actionable insights, utilizing cloud-based platforms to process structured and semi-structured data for marketing and business analytics.

What does a Data Scientist earn?

Median $173200 from 344 postings across 66 companies.

See salary data

Skills

Python SQL Machine Learning Statistical Modeling Pandas NumPy Scikit-learn Time-series Analysis Causal Inference Difference-in-Differences A/B Testing Feature Engineering Exploratory Data Analysis Data Visualization Data Integration

What you'll do

Build and interpret large-scale statistical, machine learning, and predictive models to support business decisions.
Develop and analyze Marketing Mix Models (MMM) to quantify the effectiveness of marketing investments.
Perform advanced statistical analysis including regression modeling, time-series analysis, and causal inference.
Write and optimize SQL queries and Python code to extract, transform, and analyze large datasets.
Conduct exploratory data analysis, data cleaning, and feature engineering to prepare data for modeling.
Validate and refine predictive models to ensure accuracy and robustness across new datasets.
Translate complex analytical findings into actionable business recommendations for senior leadership.
Design and evaluate controlled experiments and A/B testing methodologies for business applications.

What we're looking for

Master’s degree in a quantitative field and 1 year of analytics experience, or a Bachelor’s degree and 3 years of analytics experience.
Experience with statistical modeling and predictive analytics using regression techniques for large-scale business and marketing datasets.
Experience with Python including Pandas, NumPy, and Scikit-learn libraries for data processing, modeling, and analysis.
Experience with SQL and relational database querying for data extraction, transformation, and aggregation from large datasets.
Experience with machine learning model development, validation, and performance evaluation using standard statistical and computational techniques.
Experience with time-series analysis, forecasting techniques, and causal inference methodologies like Difference-in-Differences.
Experience with marketing and business analytics, including ROI measurement, channel contribution analysis, and A/B testing methodologies.
Experience with data visualization, reporting, and working with cloud-based data platforms for large-scale data processing.