Senior Data Scientist II, Core & Agentic Automation

This is a fully remote position, open to applicants in United States.

📋 Description

• Establish key data science priorities across various teams and determine which inquiries and investments to pursue or forgo.

• Assist in delivering the fundamental company KPI framework, including its driver tree and sensitivity modeling.

• Spearhead reusable analytical frameworks and automation for the entire company.

• Design, create, assess, and maintain analytical workflows that adhere to certified metrics to analyze KPI fluctuations, generate evidence-based hypotheses, and support subsequent analysis.

• Implement monitoring systems, failure management, and human review as necessary.

• Create reusable frameworks that incorporate evaluation and evidence traceability.

• Establish definitions and targets for certified metrics while resolving conflicting definitions with partners.

• Develop KPI trees and decompositions that link product and business drivers to MAU, retention, ARPU, revenue, and margin.

• Select justifiable models and quantify the relationships between KPIs and North Star metrics.

• Validate leading indicators outside of the sample and differentiate between arithmetic identities, predictive associations, and causal effects.

• Construct scenarios and defensible team targets.

• Set measurement standards and uphold identification assumptions.

• Choose observational methods when necessary, employing diagnostics and robustness checks.

• Assess accuracy, adoption, reduced bespoke analysis, and time to decision.

• Develop reproducible, tested analytical workflows using SQL and Python.

• Collaborate with Data Engineering on gold tables and data marts.

• Influence leadership strategy and team accountability.

• Align Finance and Product on targets, trade-offs, and evidence-driven modifications.

• Collaborate with Product, Finance, Commercial, and Engineering to enhance adoption.

• Communicate assumptions and uncertainties effectively.

• Mentor scientists and establish reusable KPI, measurement, and modeling standards that are adopted across teams.

⛳️ Requirements

• Over 8 years of experience in data science, machine learning, or applied analytics.

• Proven ownership of complex analytical challenges in product-focused environments.

• Ability to articulate the reasoning behind prioritization or rejection of questions and investments, along with their impact on planning or investment decisions.

• Capability to define KPIs and their hierarchy in collaboration with multiple stakeholders.

• Skill in structuring complex scenarios into manageable plans.

• Experience in establishing trusted metric definitions accepted across Product, Finance, Commercial, and Engineering.

• Track record of aligning Finance and Product on targets, trade-offs, and evidence-driven changes.

• Experience in selecting and validating statistical, predictive, and causal models for business planning.

• Familiarity with regression, forecasting, sensitivity analysis, and uncertainty estimation.

• Proficient in target setting and scenario planning, while differentiating between prediction and causal impact.

• Ability to set measurement standards and defend identification assumptions when randomization or causal evidence is limited.

• Sufficient experimentation knowledge to support product data scientists.

• Strong skills in SQL, Python, statistics, causal inference, and forecasting.

• Proven history of delivering reusable dashboards, diagnostic applications, or analytical frameworks with demonstrated accuracy, adoption, and decision impact.

• Experience in collaborating on the production of robust SQL/Python assets.

• History of mentoring scientists and establishing standards for KPI, measurement, or modeling.

• Practical experience in automating systems with AI, including the development and deployment of agentic automation used in actual analytical or business workflows.

• Ability to explain contributions and how an agentic system retrieves data, utilizes tools, and completes tasks.

• Proven approach to evaluating agentic systems for numerical and analytical accuracy, traceability, failure management, and adoption.

• Preferred: Experience in consumer product analytics connecting acquisition, activation, engagement, retention, and monetization.

• Preferred: Experience in owning KPI frameworks, causal measurement, or business planning across multiple teams.

• Preferred: Background in centralized or platform data science.

• Preferred: Experience with governed self-service analytics.

🏝️ Benefits

• Equity for full-time employees.

• 401(k) dollar-for-dollar match up to 4% of eligible pay.

• Comprehensive medical, dental, and vision plans, including coverage for pets.

• $10,000 per year in education reimbursement.

• Employee Resource Groups.

• Flexible PTO.

• 9 paid holidays.

• 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 with options for remote work.

• Hardware and software provided for remote work.