Job DescriptionI. Job SummaryWe are seeking a senior, full-stack Data Scientist with deep expertise in Deep learning, computer vision and agentic AI who can take complete ownership of analytics initiatives from problem definition, modeling lifecycle through executive delivery. The ideal candidate combines deep technical expertise with the ability to translate analysis into clear recommendations, anticipate stakeholder questions, and drive alignment without needing a manager to intermediate or interpret.
II. Essential Duties and Responsibilities Project Ownership and Stakeholder Communication:- Own deep learning and agentic AI initiatives end to end, from problem framing and data exploration through modeling, validation, deployment, and measurement.
- Partner directly with business and senior leaders to clarify objectives, constraints, and success criteria without relying on others to translate technical ideas. Proactively identify opportunities to apply data science to business challenges.
- Prepare and deliver executive-ready presentations that explain methodologies and recommendations, and present findings directly to stakeholders while answering questions in real time and defending technical decisions. • Independently manage priorities, scope, timelines, risks, and stakeholder expectations across multiple concurrent efforts.
Modeling and Technical Execution- Design, build, and evaluate deep learning models and agent based systems, selecting modeling approaches based on business needs, data constraints, and operational feasibility.
- Perform advanced data mining, simulation, feature engineering, and analysis on large and complex datasets.
- Translate model outputs into actionable, operational insights.
- Ensure data quality, reliability, and reproducibility; clearly communicate risks and limitations.
- Collaborate with engineering and platform teams to integrate models into production workflows.
Documentation & Knowledge Sharing - Produce clear, well-structured documentation covering problem definitions, methodologies, assumptions, results, and recommendations.
- Create artifacts (slide decks, summaries, dashboards, Confluence pages) that enable reuse without direct handholding.
- Establish and follow best practices for analytical rigor and reproducibility.
III. Qualifications A. Required Qualifications
- Bachelor's Degree (accredited) or higher in Statistics, Applied Mathematics, Operations Research, Computer Science, or related fields.
- 5 years Expeof experience applying advanced analytics or data science in a business environment. and
B. Preferred Qualifications
- Master's Degree in Statistics, Applied Mathematics, Operations Research, Computer Science, or related fields.
- Demonstrated experience owning projects independently and presenting to senior stakeholders
- Ability to integrate RL with LLM based agents, including planning, tool use, memory, and feedback loops.
- Experience in applying advanced reinforcement learning techniques including policy optimization, actor critic methods, offline RL, preference learning, and human in the loop feedback
IV. Physical RequirementsListed below are key points regarding physical demands, physical and occupational risks, and the work environment of the job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the job.☒ Office: This job primarily operates in a professional office environment and routinely requires the use of standard office equipment such as computers, phones, copy machines, etc.
V. BenefitsAt WM, each eligible employee receives a competitive total compensation package that includes medical, dental, vision, life insurance, and short-term disability. In addition, we offer a stock purchase plan, company matching on a 401(k), and more. Employees also receive paid vacation, holidays, and personal days. Please note that benefits may vary by site.
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