Senior Data Product Scientist

Job Responsibilities

• Hands-on Data Science, Modeling, and Experimentation (Primary)
• Work directly within our databases to understand data structure, mappings, lineage, quality issues, and bias; document findings and implications for analysis and product decisions.
• Write scripts to extract, transform, and analyze data to test hypotheses and validate business ideas.
• Build, test, and compare ML approaches (including GenAI where appropriate), selecting methods based on the business goal, data constraints, and evaluation criteria.
• Create reproducible workflows suitable for productization.
• Set and uphold standards for analytical rigor, reproducibility, and evaluation.
• Mentor other scientists through pairing, reviews, and practical guidance on scoping, experimentation, and communication.

Business Translation & Stakeholder Partnership

• Partner with stakeholders to understand business objectives and convert them into well-scoped data science questions.
• Translate results into decision-ready insights: what we learned, why it matters, what actions it supports, and what risks/limitations exist.
• Support executive-ready storytelling and crisp recommendations grounded in evidence.

Data Product Development (SaaS-minded)

• Use data, research, and models to help design and develop scalable data products.
• Create product briefs, requirements, and documentation that bridge business needs with technical implementation.
• Partner with engineering to develop efficient data solutions.
• Plan for future scalability (data volume growth, performance, monitoring needs, governance considerations).

Product Enablement & Training

• Train business users on how to interpret metrics, perform reporting, and convert data into insights and decisions.
• Build enablement materials (playbooks, quick-starts, definitions, case studies) to drive adoption and consistent usage.

Required QUALIFICATIONS

• Master’s Degree in STEM or Quantitative field, or 6 additional years of relevant work experience
• 8+ years of experience in applied data science
• Strong coding ability (Python and SQL expected; experience with production-grade analytics code preferred)
• Strong understanding of ML fundamentals and model evaluation; ability to choose approaches appropriately and explain tradeoffs clearly
• Ability to operate autonomously, manage ambiguity, and drive end-to-end outcomes with minimal oversight
• Strong communication and interpersonal skills; proven ability to work across technical and non-technical audiences

Preferred

• PhD in STEM of Quantitative field
• Experience building solutions intended for product scale (deployment considerations, monitoring, reliability, documentation, adoption)
• Experience with GenAI approaches (prompting patterns, evaluation, safety/quality considerations) applied to business use cases
• Experience in a “data products” environment where analytics becomes reusable, governed, and enabled across teams

Pay

The base compensation for this position is $155,000 to $185,000 commensurate with experience.

Benefits

• Medical, Dental, Vision, Prescription Drug Coverage
• 401k Plan
• Wellness Program
• Life Insurance
• Tuition Reimbursement
• Paid Time Off
• Paid Parental Leave
• Adoption Services