Senior Data Scientist: Customer Loyalty & Growth

Walmart; Hoboken (NJ); On-site; USD 108,000 - 216,000; Full time

Benefits offered by this job

Health benefits

401(k)

Stock purchase program

Life insurance

Paid time off

Job summary

Walmart in Hoboken, NJ is seeking an experienced Senior Data Scientist to leverage big data and analytics to improve loyalty and profit. You will lead data science across teams, translate insights into business strategy, and drive high-value initiatives with measurable impact.

The role emphasizes causal inference, propensity scoring, and cohort analyses, with collaboration across Data Engineering, Product, Marketing, Strategy, and Finance to inform the product roadmap and forecasts.

Qualifications

• Minimum qualifications include a Bachelor’s degree in statistics, analytics, CS or related field with 3 years analytics experience.
• Master’s degree with 1 year analytics experience or 5 years analytics experience total.
• Preferred qualifications include data science, ML, optimization models and evidence in Python/Spark/Scala/R.

Responsibilities

• Lead and execute data science for Walmart’s HighValueHabits initiatives focusing on loyalty and retention.
• Design, build, and deploy quantitative frameworks and cohort analyses.
• Lead project teams with data engineering, product, marketing, strategy and finance.
• Implement and scale best practices, including UDFs for complex logic.
• Act as SME in leadership forums and drive customer-centric culture.

Skills

Data science

Machine learning

Optimization models

Python

Spark

Scala

R

Education

Bachelor’s degree (Statistics, Economics, Analytics, Mathematics, CS, IT)

Master’s degree in related field

Tools

Python

Spark

Scala

R

Job description

Walmart in Hoboken, NJ is seeking an experienced Senior Data Scientist to leverage big data and analytics to improve loyalty and profit. You will lead data science across teams, translate insights into business strategy, and drive high-value initiatives with measurable impact.

The role emphasizes causal inference, propensity scoring, and cohort analyses, with collaboration across Data Engineering, Product, Marketing, Strategy, and Finance to inform the product roadmap and forecasts.