Senior Manager, Data Science - Last Mile Optimization

Walmart

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Bentonville, AR
Salary: $110,000–$220,000 / yr
Posted: 79 days ago
Freshness: Confirmed live yesterday
Nearby: 94 roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $191k

This role $165k

$96k most similar roles pay here $239k

This role pays less than 61% of similar roles. Most pay $157,950–$223,812 — the shaded band above. At the midpoint, this role pays about $165k versus about $191k for comparable roles.

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 184 open roles on FindRole.

Listed pay typically runs $117,000–$234,000 across 180 roles with salary data.

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At a glance

TL;DR · Senior Manager, Data Science - Last Mile Optimization

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(USA) Senior Manager, Data Science - Last Mile Optimization will join the Last-Mile Delivery team to develop advanced systems integrating artificial intelligence and scalable platforms for delivery operations. The role involves building an end-to-end operations decision optimization engine that balances supply and demand while optimizing cost to serve and service level. You will also create predictive simulation and scenario evaluation capabilities to manage demand shaping during peak events like holidays or weather disruptions. To succeed, you must possess expertise in machine learning and operations research methods, specifically linear and nonlinear programming. The required technical toolkit includes Python, R, CPLEX, and SQL for analyzing large datasets and optimizing algorithms. You will also mentor data science professionals and communicate complex technical approaches to both technical and non-technical stakeholders to solve critical logistics and forecasting challenges within the supply chain.

Skills

Operations Research Machine Learning Python CPLEX R SQL Spark Scala scikit learn TensorFlow Linear Programming Nonlinear Optimization Data Science

What you'll do

Develop an end-to-end operations decision optimization engine to balance supply and demand while optimizing cost and service levels.
Create predictive simulation and scenario evaluation capabilities for peak events like holidays, Q4, and weather.
Evaluate business cases for new projects and initiatives within the last-mile delivery space.
Communicate complex technical approaches and project updates to both technical and non-technical stakeholders.
Define and review model evaluation metrics based on specific analytical requirements.
Use Python, R, CPLEX, and SQL to analyze large datasets and optimize algorithms.
Mentor and guide data science professionals to foster technical growth and project excellence.

What we're looking for

A Bachelor’s degree in a quantitative field with 3 years of experience, a Master’s with 1 year, or 5 years of relevant experience.
PhD or Master’s degree in Operations Research, Industrial Engineering, Computer Science, Mathematics, or a related field.
8+ years of experience building optimization and machine learning models for supply chain and logistics applications.
8+ years of experience in mathematical optimization, including linear and nonlinear programming.
Proficiency in Python, R, CPLEX, and SQL to analyze large datasets and optimize algorithms.
Experience with open source frameworks such as scikit-learn, TensorFlow, or PyTorch.
Proven ability to lead data science projects and mentor other professionals.
Excellent written and verbal communication skills for presenting technical concepts to both technical and non-technical stakeholders.

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