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About the role
Key responsibilities & impact- 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.
- 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.
- 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.
Requirements
What you’ll need- Bachelor's Degree (accredited) or higher in Statistics, Applied Mathematics, Operations Research, Computer Science, or related fields.
- 5 years of experience applying advanced analytics or data science in a business environment.
- Master's Degree in Statistics, Applied Mathematics, Operations Research, Computer Science, or related fields. (preferred)
- Demonstrated experience owning projects independently and presenting to senior stakeholders. (preferred)
- Ability to integrate RL with LLM based agents, including planning, tool use, memory, and feedback loops. (preferred)
- Experience in applying advanced reinforcement learning techniques including policy optimization, actor critiquing methods, offline RL, preference learning, and human in the loop feedback. (preferred)
Benefits
Comp & perks- medical
- dental
- vision
- life insurance
- short-term disability
- stock purchase plan
- company matching on a 401(k)
- paid vacation
- holidays
- personal days
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
deep learningagent based systemsdata miningfeature engineeringadvanced analyticsreinforcement learningpolicy optimizationactor critiquing methodsoffline RLpreference learning
Soft Skills
problem framingstakeholder managementpresentation skillsindependent project ownershipcommunicationrisk managementprioritizationcollaborationanalytical rigordocumentation