(USA) Senior Data Scientist - Retail Intelligence

Key Skills

Aartificial intelligence, Algorithms, Azure, Bayesian networks, Data science techniques, Git, Google Cloud Platform (GCP), JIRA, Machine learning techniques, MLOps tools, Python Programming, PyTorch, R Programming, Scala Programming, Scikit-learn, Spark Core, TensorFlow

Job Description

Position Summary...

What you'll do...

The Senior Data Scientist in Walmart Retail Intelligence team will be core contributor in AI discovery, research, algorithmic solution design, and rapid prototyping of ML solutions to deliver efficiency in operations of Walmart US store and distribution center associates. This role will be focused on designing ML and OR models in Associate Engine that unifies associate signals to optimize workload planning and task prioritization. They will be responsible for detailed ML/AI model designs, feature engineering, model development and experimentation, and pilot testing and iterative model refinement. They will work collaboratively with Product and Tech teams to productionize and scale ML/AI solutions and establish model monitoring and management processes. This role will require partnership with other teams within the Walmart E2E Fulfillment organization (data governance, science management, retail analytics, customer engine, foundation).

The Senior Data Scientist will play a pivotal role in selection of ML/AI or Operations Research algorithms and development of them at scale, that are linked to strategic business goals, unified associate signals, efficiency of associate operations, and delivering the best associate and customer experience. They are core contributors in shaping the vision of data science work streams including prototype development cycle time, model accuracy, model reliability, model stability, coverage of use cases, decisions impact and resources cost savings

What you'll do:

• Apply broad knowledge of ML/AI capabilities to identify growth areas, new and emerging opportunities. Conducts research by studying organization goals, strategies, practices, and user projects. Recommends strategies by evaluating organization outcomes; identifying problems; evaluating trends; anticipating requirements.

• Influence a team of Data Scientists focused on powering ML/AI solutions within the scope of associate work prioritization, workforce planning and retention strategies.

• Partner closely with Data Science Management, Business Leaders, and ML engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.

• Execute full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners.

• Adhere to MLOps framework to create, build, and deploy data science algorithms continuously test and monitor drifts.

• Shares highly complex information related to areas of expertise. Interacts with senior management to keep abreast of objectives. Interacts with peers to interpret information and improve cross-functional processes and programs. Builds and enhances key internal and external contacts.

What you'll bring:

• Experience in the development of large-scale ML/AI solutions, Causal Inference and Ranking/Prioritization systems.

• 2 years+ of experience in Applied ML familiar with core supervised and unsupervised algorithms.

• Skilled in Programming language (Python) and Large-scale training using data structures and algorithms.

• 1 year+ experience with Causal Inference frameworks, Bayesian Networks and Operations Research methods (Newsvendor problem, Travelling Salesman problem, Shortest Path models, etc.)

• Experience with cloud environments including Azure, Google Cloud, etc.

• Solid MLOps practices including good design documentation, unit testing, integration testing and source code control (git).

• Experienced with agile methodologies using project planning and tracking management tools e.g., JIRA.

Flexible, hybrid work:

We use a hybrid way of working that is primarily in office coupled with virtual when not onsite. Our campuses serve as a hub to enhance collaboration, bring us together for purpose and deliver on business needs. This approach helps us make quicker decisions, remove location barriers across our global team and be more flexible in our personal lives.

Benefits:

Benefits: Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much more.

Equal Opportunity Employer

Minimum Qualifications...

Outlined 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 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, 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 Location...

702 SW 8TH ST, BENTONVILLE, AR 72716, United States of America.