(USA) Principal Data Scientist - Retail Intelligence

Key Skills

A/B Testing, Aartificial intelligence, Algorithms, Azure, Bayesian networks, Data science techniques, Databricks, Git, Google BigQuery, Google Cloud Platform (GCP), JIRA, Leadership, Machine learning techniques, MLOps tools, NumPy, Pandas, Python Programming, PyTorch, R Programming, Retail , Scala Programming, Scikit-learn, Spark Core, Statistics, TensorFlow

Job Description

Position Summary...

What you'll do...

The Principal Data Scientist in Walmart Retail Intelligence team will drive AI discovery, research, algorithmic solution design, and rapid prototyping targeted to deliver important activations within Walmart US. This role will be focused on operational and execution decision engines with alignment to unified associate signals and workload optimization supported by Retail Science Associate team. They will be responsible for high level ML/AI conceptualization, feature engineering, ML/AI 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 Principal Data Scientist will play a pivotal in deciding how do we develop ML/AI algorithms, at scale, that are linked to strategic business choices, unified associate signals, efficiency of associate operations, and delivering the desired associate, customer, and/or financial impact. They own the vision on improving efficiency 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 AI/ML 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.

• 6 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.

• 2 years+ 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.

About Walmart Global Tech

Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered. We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.

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:

Walmart, 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.

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 responsibilities and qualifications required of employees assigned to this job. The full Job Description can be made available as part of the hiring process.

*Job Ad Ends*

Minimum and Preferred Qualification will be pulled in from the Workday Profile.

Please do not add additional Minimum and Preferred Qualification sections.

Additional comments from the hiring manager: Minimum Qualifications: Option 1: Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 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 4 years' experience in analytics related field. Option 3: 8 years' experience in an analytics or related field Preferred Qualifications: 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, using open source frameworks (for example, scikit learn, TensorFlow, torch) with 6 years+ of experience post graduate degree.

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, Publications or active peer reviewer in related journals or conference, 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