Position SummaryWhat you'll doWe are looking for an enthusiastic, creative Senior Data Scientist to join Investigative Risk and Operational Compliance Center (IROCC) team. You will be responsible to solve complex business problems using innovative data mining, machine learning and optimization techniques. You will be a part of a cross-functional team of Data Analysts and Scientists focusing on solving business problem in the Ethics and Compliance subject area. This role reports to the Director, Data Analytics.What You'll Do:
Be a strategic team member of the IROCC teams, sharing insights and providing recommendations through effective communication and storytelling with data.
Translate business requirements to technical solutions in machine learning models, analysis, or software tools
Share use cases and gives examples to demonstrate how the method would solve the business problem.
Build complex data sets from multiple data sources, both internally and externally
Process complicated and large-scale datasets using distributed computing platforms; extract insights from data.
Identify dimensions of the experiment, finalizes the design, tests hypotheses, and conducts the experiment
Design, build, and implement predictive and optimization models for replication of future projects
Identify the model evaluation metrics
Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity , and robustness for multi-stage models and model ensembles
Create test cases to review and validate the proposed solution design.
Demonstrate incremental solution approach with agile and flexible ability to overcome the practical problems
Productionize solutions (such as in the form of model servers or cron jobs); maintain and continuously improve the solutions; address production issues. Present on projects within team or beyond to boost knowledge sharing, visibility, and business impact.
Write solid production code, mainly in Python. Master and help evolve the team's technical stack (centered on Python, cloud, ML/DL, Docker, Kubernetes); understand Walmart's product, data and pipeline systems.
Participate in project and model discussions, code reviews. Assist the team on system, infrastructure, analytics, modeling, and other needs.
What You'll Bring:
3+ years (with Masters' degree) or 1+ years (with PhD degree) programming-heavy work experience in a software engineering or data science team.
Experience with creating R Shiny apps is a plus
Technical expertise in data mining, machine learning, and statistical analysis(Python/PySpark/R/SQL)
An extensive background in AIML methods including LLMs, NLP, CNN, RNN, transfer learning, attention mechanisms, large language models, transformers, generative models and embedding methods
Work experiences using "traditional" machine learning models such as classification, clustering, random forest, boosting, and ensemble to solve real-world problems.
Experience using data visualization (PowerBI/Tableau/Matplotlib) to derive powerful insights
Decent proficiency at major ML and DL libraries such as scikit-learn, pytorch, tensorflow, numpy.
Experience working with large data sets and distributed computing tools (Map/Reduce, Hadoop, Hive, or Spark)
The above information has been designed to indicate the general nature and level of work performed in the role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job. The full Job Description can be made available as part of the hiring process.Benefits & Perks:Beyond competitive pay, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, FlexTO, multiple health plans, and much more.Equal Opportunity EmployerWalmart, 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, ideas and opinions - while being inclusive of all people.Who We AreJoin Walmart and your work could help 220 million global customers live better every week. Yes, we are the Fortune #1 company. But you'll quickly find we're a company who wants you to feel comfortable bringing your whole self to work. A career at Walmart is where the world's most complex challenges meet a kinder way of life. Our mission spreads far beyond the walls of our stores. Join us and you'll discover why we are a world leader in diversity and inclusion, sustainability, and community involvement. From day one, you'll be empowered and equipped to do the best work of your life. careers.walmart.comMinimum QualificationsOutlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.Option 1- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field. Option 2- Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field. Option 3 - 5 years' experience in an analytics or related field.Preferred QualificationsOutlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.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)Primary Location2914 Se I St, Bentonville, AR 72712-3148, United States of AmericaWalmart, 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.