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Position Summary...

What you'll do...

About The Walmart Marketplace Decision Management Team

Walmart’s Decision Management Team supports the growth of the e-Commerce

Marketplace program through the practical application of data science and advanced

analysis to optimize risk decision strategies. This includes data analysis, advanced

statistics, case investigation and application of advanced modeling techniques to

manage risk on the ecommerce platform. We work alongside business, product, and

engineering teams to deliver solutions to manage Marketplace risk.

What You'll Do…

The Senior Manager, DataScience will lead a team of data scientists to define,

implement, test, and deploy decision strategies aimed at mitigating fraud and

performance risks for Walmart Marketplace. In this role, you will work closely with cross-

functional teams, including product, engineering, and data science, to continuously

monitor, investigate, and respond to emerging risk trends. You’ll be responsible for

leveraging advanced data science methodologies to develop and refine risk

management models, ensuring the strategies are effective and scalable across both

domestic and international portfolios.

How You'll Make an Impact:

• Drive Data Science Innovation to protect the integrity of the Marketplace by applying

advanced statistical methods, machine learning, and AI techniques to identify and

mitigate fraud and performance risks.

• Support Marketplace Growth by designing and implementing scalable, data-driven risk

management solutions that align with key business objectives and growth targets.

• Provide technical leadership and mentorship to your team, overseeing the

development of decision models, managing model performance, and ensuring they

are optimized for both accuracy and scalability.

• Apply Advanced Data Science Techniques such as predictive modeling, supervised

and unsupervised machine learning, deep learning, and anomaly detection to

continuously improve risk strategies.

• Collaborate Across Teams to integrate data science models with business processes,

ensuring alignment between product, engineering, and data teams to address key risk

areas effectively.

• Monitor the performance of deployed models, identify opportunities for improvement,

and iterate to enhance their predictive power and robustness in mitigating risks.

• Develop Test & Measurement Frameworks to validate model effectiveness, utilizing

rigorous A/B testing, statistical testing, and model evaluation to refine decision

strategies.

• Foster Innovation by exploring cutting-edge data science techniques, identifying

opportunities to optimize decision-making, and driving improvements in risk

management capabilities.

What You'll Bring:

• Deep understanding of machine learning, statistical modeling, and data science

techniques used for risk mitigation in e-commerce or marketplace environments.

• Proven ability to build, deploy, and optimize complex data science models to identify

and mitigate fraud, performance, and operational risks.

• Proficiency in tools and languages such as Python, R, Spark, Scala, and machine

learning frameworks (e.g., TensorFlow, PyTorch, XGBoost) to develop and deploy risk

models.

• Ability to understand the end-to-end risk management process, from data ingestion

and feature engineering to model deployment and real-time decision making.

• 5-8 years of experience in leading teams or projects related to data science, including

mentoring junior data scientists and guiding technical teams toward best practices in

model development and deployment.

• Comfortable navigating complex and uncertain situations, making data-driven

decisions to improve risk management strategies in a fast-evolving environment.

• Strong ability to translate complex data science concepts into clear, actionable insights

for non-technical stakeholders across the organization.

• Understanding how data science and risk management intersect with broader

business objectives and the ability to align risk strategies with organizational goals.

Minimum Qualifications:

• Option 1: Bachelor’s degree in Statistics, Computer Science, Data Science,

Mathematics, or related field, with 5-8 years of hands-on experience in data science,

machine learning, or risk management.

• Option 2: Master’s degree in a related field (e.g., Data Science, Machine Learning,

Statistics, Applied Mathematics) with at least 3-5 years of applied experience working

on data-driven risk management or fraud prevention.

• Option 3: 8-10 years of direct experience in data science, machine learning, or applied

risk management within an e-commerce or marketplace setting.

Preferred Qualifications:

• Expertise in using advanced machine learning techniques such as deep learning,

reinforcement learning, or anomaly detection for fraud detection or risk mitigation.

• Experience with big data technologies like Apache Spark, Hadoop, and cloud-based

data solutions (e.g., AWS, Google Cloud) to build scalable risk management

platforms.

• Proficiency in data manipulation and analysis tools such as Pandas, NumPy,

and SQL for data wrangling, feature engineering, and analysis.

• Strong background in model evaluation techniques including ROC/AUC, confusion

matrices, precision/recall, and F1 scores, as well as experience with A/B testing and model validation.

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Minimum Qualifications...

_Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.

Preferred Qualifications...

_Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.

Primary Location...

702 Sw 8Th St, Bentonville, AR 72716, United States of America

Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

Walmart, Inc. is an Equal Opportunity Employer- By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, abilities, ideas and opinions- while being inclusive of all people.