Senior Data Scientist

Walmart • Hoboken, NJ

6d

About The Position

The Senior Data Scientist develops and implements advanced data science and artificial intelligence solutions to support business decision-making. The role builds, analyzes, and interprets statistical, machine learning, predictive, and large-scale analytical models, including Marketing Mix Models, to evaluate business performance, quantify marketing effectiveness, and identify optimization opportunities. It applies statistical methods such as regression and time-series analysis, develops and validates predictive models, processes large volumes of structured data, and uses SQL, Python, and cloud-based data platforms to analyze datasets. The position also prepares data through exploratory analysis, validation, cleaning, and feature engineering; collaborates with cross-functional teams to translate business needs into analytical frameworks; communicates findings and recommendations to stakeholders and senior leadership; and applies emerging data science and AI techniques to improve methodologies and business outcomes.

Requirements

• Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering, Applied Data Science, or a related field, and at least 1 year of experience in an analytics-related field; OR a bachelor’s degree or equivalent in one of these fields and at least 3 years of experience in an analytics-related field.
• Experience with statistical modeling and predictive analytics using regression techniques on large-scale business and marketing datasets.
• Experience with Python, including Pandas, NumPy, and Scikit-learn.
• Experience with SQL and relational database querying to extract, transform, and aggregate large datasets.
• Experience with exploratory data analysis, data cleaning, and feature engineering.
• Experience developing, validating, and evaluating machine learning models.
• Experience with time-series analysis and forecasting.
• Experience with causal inference and quasi-experimental methods, including Difference-in-Differences.
• Experience with marketing and business analytics, including return-on-investment measurement and channel contribution analysis.
• Experience integrating and handling large datasets from multiple sources, including structured and semi-structured data environments.
• Experience with data visualization and reporting to communicate insights and support decision-making.
• Experience designing and evaluating controlled experiments and A/B tests for business applications.
• Experience working with cloud-based data platforms for storage, processing, and analysis of large datasets.

Responsibilities

• Develop and implement data science and artificial intelligence solutions to support business decision-making.
• Build, analyze, and interpret statistical, machine learning, predictive, and large-scale analytical models.
• Evaluate business performance and identify key drivers of outcomes, including the impact of marketing and business initiatives.
• Build and evaluate Marketing Mix Models to measure marketing investment effectiveness, campaign performance, and optimization opportunities.
• Perform regression modeling, time-series analysis, and other statistical and machine learning analyses to quantify trends, relationships, and business impact.
• Develop, train, validate, refine, and evaluate predictive models and algorithms.
• Apply AI and machine learning techniques to large volumes of structured data and scalable analytical problems.
• Write and optimize SQL queries and use Python to extract, transform, and analyze large datasets.
• Conduct exploratory data analysis, data validation, data cleaning, and feature engineering.
• Use large-scale data environments and cloud-based platforms to process and analyze data.
• Collaborate with cross-functional teams to understand business requirements, create analytical frameworks, and deliver insights and recommendations.
• Communicate analytical findings to stakeholders, including senior leadership, and translate insights into business actions.
• Research and apply industry best practices and emerging data science, machine learning, and AI techniques.

Benefits

• Medical, vision, and dental coverage.
• 401(k).
• Stock purchase plan.
• Company-paid life insurance.
• Paid time off, including sick leave.
• Parental leave.
• Family care leave.
• Bereavement leave.
• Jury duty and voting leave.
• Short-term and long-term disability.
• Education assistance, including company-paid college degrees.
• Company discounts.
• Military service pay.
• Adoption expense reimbursement.
• Performance-based incentive awards and annual or quarterly performance incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior