Senior Data Science Manager

Role Overview

• Lead a team of data scientists, identifying strengths and development areas to foster a collaborative and inclusive environment.
• Own talent strategy and career development, providing one on one coaching, facilitating access to training, and delivering advice to help team members advance from individual contributors to technical leaders.
• Drive the recruiting and retention of top data science talent, ensuring the team's growth aligns with the scaling needs of the initiative.
• Serve as the end to end owner of project delivery, managing resources, timelines, and the operational cadence from inception to completion.
• Act as a primary interface for stakeholders, prioritizing initiatives to protect the roadmap and ensuring the team hits high impact milestones on time.
• Collaborate with Product Management and peer partners to define and execute technical roadmaps, ensuring data science capabilities are integrated into the core platform strategy.
• Drive the end-to-end realization of unique AI initiatives, taking your own ideas and stakeholder needs from initial concept through to production-level GenAI, vision, and forecasting solutions.
• Serve as the final technical sign off for the team's output, reviewing and approving technical approaches to ensure they are sound, scalable, and align with project goals.
• Maintain a hands-on presence by contributing to code performance optimization, data engineering, and quality assurance to ensure production level reliability.
• Partner with the Senior Principal Data Scientist to bridge the gap between prototyping and production scale execution, translating high level technical vision into actionable software design.
• Collaborate with Engineering to ensure data sources and infrastructure are designed to support production level machine learning and custom reporting.

Requirements

• 5+ years of experience in data science or analytics roles with demonstrated progression in scope and responsibility.
• 2+ years of leadership experience, specifically in managing data science teams, recruiting talent, and retaining top performers.
• Strong proficiency in Python and SQL for data manipulation, analysis, and code review.
• Experience with managing complex, large-scale data science projects from inception to production.
• Familiarity with the AI/ML lifecycle, including understanding model experimentation, monitoring, and maintenance in a production setting.
• Exposure to modern AI domains, such as Generative AI, Large Language Models (LLMs), Computer Vision, or multimodal embedding models is highly preferred.
• Bachelor's degree or higher in a quantitative discipline (Statistics, Mathematics, Computer Science, or related field).
• Excellent communication skills, with the ability to distill complex ML concepts into practical industry applications for non-technical leadership.

Tech Stack

• Python
• SQL

Benefits

• medical
• dental
• vision
• PTO
• generous employee discounts
• retirement savings
• much more!