Associate Data Scientist building predictive models and AI applications for AlgaeCal’s clinically - backed natural bone - loss solution. Transforming data into strategies that improve efficiency, sales, and profitability.
About the role
- Senior Data Scientist building KPI frameworks and agentic analytical automation for Fetch’s rewards platform. Driving trusted metrics, causal measurement, and cross-functional business decisions.
Responsibilities
- Define core data science priorities across teams and decide which questions and investments to pursue or decline
- Help deliver the core company KPI framework, including its driver tree and sensitivity modeling
- Lead reusable, company-wide analytical frameworks and automation
- Design, build, evaluate, and maintain agentic analytical workflows using certified metrics to investigate KPI changes and generate evidence-backed hypotheses
- Implement monitoring, failure handling, and human review where needed
- Design reusable frameworks with evaluation and evidence traceability
- Set definitions and targets for certified metrics and resolve conflicting definitions with partners
- Build KPI trees and decompositions connecting product and business drivers to MAU, retention, ARPU, revenue, and margin
- Select defensible models and quantify KPI-to-North-Star relationships
- Validate leading indicators out of sample and distinguish arithmetic identities, predictive associations, and causal effects
- Build scenarios and defensible team targets
- Set measurement standards and defend identification assumptions
- Select observational methods and use diagnostics and robustness checks
- Measure accuracy, adoption, reduced bespoke analysis, and time to decision
- Build reproducible, tested analytical workflows in SQL and Python
- Partner with Data Engineering on gold tables and data marts
- Shape leadership strategy and team accountability, aligning Finance and Product on targets and trade-offs
- Partner with Product, Finance, Commercial, and Engineering to drive adoption
- Communicate assumptions and uncertainty clearly
- Mentor scientists and establish reusable KPI, measurement, and modeling standards across teams
Requirements
- 8+ years of experience in data science, machine learning, or applied analytics
- Demonstrated ownership of complex analytical problems in product-driven environments
- Ability to explain prioritization of questions and investments and their impact on planning or investment decisions
- Ability to define KPIs and hierarchies with multiple stakeholders
- Ability to structure complex spaces into tackle-able plans
- Experience establishing trusted metric definitions across Product, Finance, Commercial, and Engineering
- Track record aligning Finance and Product on targets, trade-offs, and evidence-based changes
- Experience selecting and validating statistical, predictive, and causal models, including regression, forecasting, sensitivity analysis, and uncertainty estimation
- Ability to use models for target setting and scenario planning while distinguishing prediction from causal impact
- Experience setting measurement standards and defending identification assumptions when randomization or causal evidence is limited
- Experimentation knowledge sufficient to support product data scientists
- Strong skills in SQL, Python, statistics, causal inference, and forecasting
- Track record shipping reusable dashboards, diagnostic apps, or analytical frameworks with proven accuracy, adoption, and decision impact
- Experience partnering on productionization of robust SQL/Python assets
- History of mentoring scientists and establishing KPI, measurement, or modeling standards
- Hands-on experience automating systems with AI, including personally building and shipping agentic automation used in analytical or business workflows
- Ability to explain system contributions, data retrieval, tool use, and task completion
- Experience evaluating agentic systems for numerical and analytical accuracy, traceability, failure handling, and adoption
- Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization (preferred)
- Experience owning KPI frameworks, causal measurement, or business planning across multiple teams (preferred)
- Experience in centralized or platform data science (preferred)
- Experience with governed self-service analytics (preferred)
- Appropriate work authorization for the United States or Canada
Benefits
- Equity for full-time employees
- 401(k) with dollar-for-dollar matching up to 4% of eligible pay
- Comprehensive medical, dental, and vision plans, including pets
- Ten thousand per year in education reimbursement
- Employee Resource Groups and Inclusion Council participation
- Flexible PTO
- 9 paid holidays (holidays vary for Canada-based roles)
- Year-end week-long break
- 14 weeks of fully paid parental leave
- 6 additional weeks of paid childbirth recovery leave for birthing parents
- Flexible return-to-work schedule
- One-time $2,000 Calvin Care Cash incentive for employees welcoming new family members
- Flexible work environment
- Hardware and software provided for remote work
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