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Staff Data Scientist
3 months ago
At Walmart Advanced Systems & Robotics, we're building the infrastructure that will power the next generation of retail experiences. We're the team behind Alphabot®, a new technology that's changing the way America shops. Our automated pickup and delivery systems use a combination of robotics and software to efficiently handle large volumes of online orders, streamlining operations for managers and enhancing the customer experience. We're passionate about technology, retail, and creating solutions that impact millions of customers daily.
We are seeking a customer-focused data scientist or machine learning scientist to lead the development of predictive maintenance technologies for a fleet of autonomous mobile robots. We are looking for critical thinkers with a passion for analyzing data and uncovering insights from large, complex engineered systems, and delivering complete data products to stakeholders.
The position is aimed towards a specialist in the domain of predictive maintenance. An ideal candidate has deep knowledge of data driven models and has experience working with time series data collected from sensors on physical systems. Relevant modeling experience includes development of time series anomaly detectors, remaining useful life estimators, or predictive maintenance recommenders.
As a core member of a data science and machine learning team, you will work on research, development, implementation and productization of systems that guide maintenance decisions.
The ideal candidate holds a PhD with 2+ year's experience (or an MS with 5+ year's experience) in Engineering (mechanical, electrical, reliability, etc.), Applied Mathematics, Statistics or Physics.
WHAT WE'RE LOOKING FOR:- Develop models and algorithms that support making data driven maintenance decisions that anticipate and preempt hardware faults.
- Define for self and potentially others the work needed to deliver high quality maintenance recommendations.
- Participate in early stage development to shape the architecture of predictive maintenance services.
- Collaborate with software development teams to implement and deploy models and algorithms.
- Build scripts to collect, clean, transform and join large sources of data.
- Write Python applications as a containerized artefact, and deployed to kubernetes environments.
- Negotiate product requirements with stakeholders, manage project roadmaps and deliverables, report progress to leadership.
PREFERRED, BUT NOT REQUIRED:
- PhD (preferred) or MS in Mechanical/Electrical/Reliability Engineering, Applied Mathematics, Statistics or Physics.
- 2-5 years of post-graduate experience.
- Deep knowledge in signal processing and time-series anomaly detection.
- Preferred knowledge in reliability engineering and quality manufacturing.
- Experience with the data manipulation functions of time series analysis: cleaning, imputing, resampling, frequency-domain filtering, and visualization.
- Experienced with machine learning modeling techniques such as linear and non-linear regression, RNN/LSTM, markov chains; and model-based estimation techniques like Kalman Filtering, Receding Horizon Estimators and Particle Filters.
- Proficient in Python, MATLAB, R or Julia. Experienced in traditional and deep learning frameworks in the associated language.
- Familiarity with query languages (SQL, KQL, etc), cloud environments (Azure, AWS, GCP) and modern software development tools and processes (source control with git, unit/integration tests, CI/CD, serverless deployment with kubernetes).
- Comprehensive health, vision, and insurance plans with options for dependent coverage
- Unlimited PTO for salaried employees, covering vacation, holidays, and personal days
- Competitive 401(k) matching program, stock purchase plans, and equity opportunities
- Up to 12 weeks of fully paid maternity/paternity leave
- Special Walmart discounts for in-store and online purchases
- Complimentary daily lunches, beverages, and snacks
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, abilities, ideas and opinions – while being inclusive of all people.
