Senior Machine Learning Scientist
QlooSalary not specified
Full Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
E-Commerce, Retail, Risk ManagementIndustries
Requirements
- Strong understanding of machine learning, data exploration, statistical modeling, and their application to risk and fraud detection in digital marketplaces
- Demonstrated experience developing and deploying models to identify anomalous behavior, detect fraud, or assess risk in real-time systems
- Proficiency in Python, SQL, and data science libraries/frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch
- Familiarity with Agentic AI systems or AI agents—understanding of how autonomous models can be leveraged in dynamic decision environments
- Experience conducting experimentation and model validation using rigorous statistical methods (e.g., A/B testing, ROC/AUC, precision/recall)
- A strong problem-solving mindset and ability to translate ambiguous business problems into clear analytical frameworks
- Excellent written and verbal communication skills, with the ability to explain technical concepts to diverse audiences
- Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn) to craft compelling insights
- Option 1: Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or related field, with 5+ 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 [specified years, text cut off]
Responsibilities
- Develop Risk Mitigation Models using machine learning, anomaly detection, and statistical techniques to identify and respond to emerging risk trends on the Marketplace platform
- Analyze Risk Patterns by exploring large datasets to uncover emerging fraud tactics, behavioral anomalies, and areas of business exposure
- Develop Predictive Models using supervised and unsupervised learning techniques to power risk detection systems at scale
- Lead Deep-Dive Analytics to inform risk policy, product decisions, or operational strategies—identifying key drivers, trends, and optimization opportunities
- Integrate Agentic AI Frameworks to support semi-autonomous risk detection systems that can adapt and respond to evolving fraud patterns in real-time
- Explore Generative AI (GenAI) Applications for synthetic data generation, anomaly simulation, or scenario modeling to improve risk model robustness
- Collaborate Cross-Functionally with product, engineering, and operations teams to ensure seamless integration of data science solutions into business workflows
- Monitor Model Performance and proactively identify areas for improvement using quantitative metrics, feedback loops, and model diagnostics
- Bridge Analytics and Science by combining robust data analysis with model development to create solutions that are both explainable and effective
- Translate Insights into Action by communicating complex analytical findings clearly to both technical and non-technical stakeholders
- Design and Execute Experiments (e.g., A/B tests, statistical validations) to evaluate model impact and improve decision strategies
Skills
Machine Learning
Anomaly Detection
Statistical Techniques
Supervised Learning
Unsupervised Learning
Predictive Modeling
Generative AI
Agentic AI
Data Analysis
SQL
Python
Scalable Models
Walmart
Global retail chain offering affordable products
About Walmart
Walmart operates a chain of hypermarkets, discount department stores, and grocery stores, providing a wide variety of products at low prices to everyday consumers, families, and communities. The company combines physical retail locations with an e-commerce platform, allowing customers to shop for groceries, apparel, electronics, and household items both in-store and online. Walmart's efficient supply chain management and large-scale purchasing enable it to maintain affordability, setting it apart from competitors. The company also offers financial services and health and wellness services, including pharmacies and vision centers. Walmart's goal is to save people money and support communities, as demonstrated by its efforts during the COVID-19 pandemic and its commitment to social responsibility, including programs for veterans and military families.
Bentonville, ArkansasHeadquarters
1962Year Founded
$5,515MTotal Funding
IPOCompany Stage
Financial Services, Consumer GoodsIndustries
10,001+Employees
Benefits
PTO: Paid vacation, sick time, personal time and holiday time
10% discount on regularly priced general merchandise and fresh fruits and vegetables
6% 401(k) match to all employees, including hourly workers, after one year
Roth IRA available
Associate Stock Purchase Plan
maximum and eligible preventive care covered at 100%
Health reimbursement plans
Risks
Rising U.S. labor costs could pressure profit margins.
Amazon's grocery delivery expansion threatens Walmart's market share.
Fintech investments expose Walmart to financial regulatory risks.
Differentiation
Walmart's omnichannel strategy integrates physical and online retail seamlessly.
The company offers a wide range of products at consistently low prices.
Walmart's commitment to community support enhances its brand reputation.
Upsides
Walmart's investment in fintech expands its financial services offerings.
Robotics integration in distribution centers boosts operational efficiency.
Culturally themed product lines attract diverse customer segments.
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