Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Senior Data Scientist, AI Product Insights role.

Rezi rewrites your resume against Mixpanel's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Senior Data Scientist, AI Product Insights posting at Mixpanel — free, in seconds.

About the Role

As the first Data Scientist embedded in product engineering, you'll champion integrating cutting-edge data science techniques into Mixpanel's products and serve as a methodological resource for cross-functional teams tackling problems that benefit from deeper DS expertise. Your models will be the reasoning layer behind an AI system that proactively tells customers what changed, why, and what to do next. You'll design and validate causal inference approaches and partner on how those outputs get translated into clear, natural-language, actionable experiences for customers. This is a high-impact, high-autonomy role on a small, fast-moving team with significant influence over the analytical direction of a new product category.

Responsibilities

Own the end-to-end analytical design for Signals, Forecasting, Simulation, and Cohort Detection — including methodology selection, statistical validation, and iteration based on results
Assess data quality and trust prerequisites before extending forecasting or predictive features to customers
Design and apply causal inference methods to move beyond correlation and establish which user behaviors genuinely drive downstream business outcomes
Build and own time-series forecasting models that project KPI trajectories against goals
Build survival analysis and retention models that underpin Signals and Simulation outputs
Develop clustering and behavioral similarity approaches for Cohort Detection that are both statistically sound and interpretable to end users
Document methodology clearly — including assumptions, validation approaches, and expected output behavior
Review and validate that production results match expected statistical behavior, partnering with engineers on edge cases and anomalies
Establish rigor around statistical significance, multiple testing correction, and uncertainty quantification
Work cross-functionally with internal stakeholders, including Finance and Data Science, to ensure analytical outputs are grounded in real business outcomes
Communicate findings and methodology clearly to Product and Engineering — translating statistical concepts into plain language

Requirements

MS or PhD in Statistics, Economics, Mathematics, or a related quantitative field — or equivalent industry experience with demonstrated causal inference expertise
5+ years of experience applying statistical modeling to real-world product or business problems
Hands-on causal inference experience — propensity score matching, regression discontinuity, difference-in-differences, or instrumental variables — with the judgment to choose the right method for a given problem
Experience with survival analysis or retention modeling (e.g. Cox proportional hazards, Kaplan-Meier)
Strong Python fluency across the analytical stack — statsmodels, scikit-learn, pandas, and equivalent libraries for survival analysis, clustering, and time-series modeling
Experience with time-series forecasting methods — classical approaches (ARIMA, exponential smoothing) and/or modern foundation models such as TimesFM, Chronos, or similar
Experience with clustering and similarity methods applied to behavioral or user data
Strong statistical communication — you can explain a propensity score or a survival curve to a PM without losing them
SQL fluency for data access, exploration, and validation
Comfort working in a product environment where analytical rigor and practical delivery go hand in hand
Experience working with large-scale behavioral event data (product analytics, growth, or similar domains)
Familiarity with feature engineering from raw event streams
Experience with structural equation modeling or causal DAGs for multi-metric impact modeling (directly applicable to Simulation)
Familiarity with how offline batch analyses are productionized, even if you're not implementing them yourself
Comfort working directly in a production codebase alongside engineers
Experience at an analytics, observability, or growth platform
Experience evaluating or grounding LLM-generated explanations or recommendations against statistical outputs (e.g. hallucination or consistency checks on AI-generated insights)
Comfort using AI coding tools (Claude Code, Cursor, etc.) to accelerate modeling iteration

Skills

Causal inference
Survival analysis
Retention modeling
Python
statsmodels
scikit-learn
pandas
Time-series forecasting
Clustering
Behavioral similarity
Statistical communication
SQL
LLM evaluation
AI coding tools

Location

Work Type

Full-time

Experience Level

5+ years

Education Level

MS or PhD in Statistics, Economics, Mathematics, or a related quantitative field

Salary/Compensations

$226,000—$266,000 USD

Benefits

Comprehensive Medical, Vision, and Dental Care
Mental Wellness Benefit
Generous Vacation Policy & Additional Company Holidays
Enhanced Parental Leave
Volunteer Time Off
Pre-Tax Benefits including 401(K)
Wellness Benefit
Holiday Break

About the Company

Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build.
By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next.
We’re a leader in analytics with over 9,000 customers and $277M raised from prominent investors: like Andreessen-Horowitz, Sequoia, YC, and, most recently, Bain Capital.
Mixpanel’s pioneering event-based data analytics platform offers a powerful yet simple solution for companies to understand user behaviors and easily track overarching company success metrics.
Our accomplished teams continuously facilitate our expansion by tackling the ever-evolving challenges tied to scaling, reliability, design, and service.
Choosing to work at Mixpanel means you’ll be helping the world’s most innovative companies learn from their data so they can make better decisions.

Equal Opportunity

Mixpanel is an equal opportunity employer supporting workforce diversity.
We actively encourage women, people with disabilities, veterans, underrepresented minorities, and LGBTQ+ people to apply.
We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status.
Pursuant to the San Francisco Fair Chance Ordinance or other similar laws that may be applicable, we will consider for employment qualified applicants with arrest and conviction records.