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.