Data Scientist.
Prefer a candidate with more ML modeling experience.
Qualifications
Solid background in machine learning, deep learning, statistical analysis, and software development
Proficient in data mining, machine learning, and deep learning packages in Python/Tensorflow/Keras
Experience working with large data sets and cloud computing (Hive, Spark, GCP, or Azure)
Proficient in coding SQL, Python, Java, or JavaScript
Advanced degree (Master or PhD) in any STEM field plus 4~6 years of related experience
Option 1- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3
Information Technology, or related field and 1 years' experience in an analytics related field
Option 3 - 5 years' experience in an analytics or Data science, machine learning, optimization models, Master's degree 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, 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
Responsibilities
Perform hands-on data exploration, processing, and analysis on massive data sets
Use machine learning, deep learning, reinforcement learning techniques to develop robust solution for Account Takeover detection, payment fraud detection, fake account signup solutions and identity risk assessment
Communicate the results to stakeholders and present the projects in internal or external conferences
Research and develop advanced algorithms and techniques that address complex business problems
Utilize the broad and deep knowledge of Machine Learning and Software Engineering to contribute to the team's core machine learning capabilities
ML senior engineers
Technical Skills
Must have:
Expertise in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
Strong Experience in deployment/devops technologies: CI/CD pipelines, Kubernetes/Docker, and infrastructure-as-code tools (Terraform, Ansible, etc.). and cloud-native architectures (GCP and Aruze), monitoring and observability for ML workloads
Advanced understanding of ML pipeline orchestration tools like Kubeflow, MLflow, Airflow, or TFX.
Nice to have:
Experience with distributed computing frameworks (e.g., Spark, Ray, Dask) is a plus.
Familiarity with model explainability, fairness, and bias detection tools is highly desirable.
Strong knowledge of security best practices for ML systems, including data encryption, API security, and governance.
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