Senior Data Scientist, AI Product Insights

About Mixpanel

Mixpanel is the leading product intelligence and analytics platform trusted by more than 29000 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 whats working diagnose whats not and decide what to build next. Learn more at .

The Proactive Insights team is a newly formed team at the center of Mixpanels AI-first analytics vision. With a greenfield charter were building the intelligent layer that transforms Mixpanel from a tool you query into a partner that works for you.

We answer the question every data-driven team asks: What changed why and what should I do about it We proactively keep users informed about what matters in their data delivering the right insights and recommendations at the right time to the right places both inside and outside of Mixpanel.

Some examples of what we are building:

• Signals: Statistical analysis that automatically identifies which user behaviors cause downstream business outcomes such as which actions genuinely improve 30-day retention using causal inference to move beyond correlation
• Forecasting: Time-series modeling that projects whether a KPI (e.g. Signups) will hit its goal by end of quarter including trend decomposition seasonality adjustment and confidence bands against a target.
• Simulation: Causal impact modeling that estimates how moving one metric (e.g. weekly sharing rate) by a given amount will ripple through to downstream KPIs like retention or revenue giving teams a quantified basis for prioritization
• Cohort Detection: Automated identification of at-risk user cohorts by finding active users who resemble known churned segments across both behavioral patterns and descriptive characteristics before they churn. Offline batch survival analysis models that estimate each users probability of a future outcome (e.g. likelihood to churn or convert within 30 days).

As the first Data Scientist embedded in product engineering youll champion integrating cutting-edge data science techniques into Mixpanels products and serve as a methodological resource for cross-functional teams tackling problems that benefit from deeper DS expertise such as adaptive experimentation. You wont just advise on Proactive Insights; youll be the analytical brain driving how Signals Forecasting Simulation Predictions and Cohort Detection actually work.

Your models are the reasoning layer behind an AI system that proactively tells customers what changed why and what to do next and increasingly the layer behind an agent that acts on their behalf. As more of this experience becomes agentic rigorous causal grounding is what separates a trustworthy recommendation from a plausible-sounding one. Youll be the person who makes sure its the former.

Youll design and validate causal inference approaches that go beyond surface-level correlation and partner on how those outputs get translated often via LLMs into clear natural-language actionable experiences for Mixpanels customers: you own the rigor the system owns the explanation. Youll partner closely with strong product engineers who own the implementation your job is to make sure the methodology is rigorous well-documented and grounded in real outcomes. Youll also collaborate cross-functionally with teams like AI platform analysis and data infrastructure to scale your analytic solutions beyond what you could build alone.

This is a high-impact high-autonomy role on a small fast-moving team. Youll have significant influence over the analytical direction of a new product category at Mixpanel that helps thousands of companies understand what truly drives their most important metrics.

• 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 a model is only as trustworthy as the data feeding it
• 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 extending our existing use of TimesFM into customer-facing forecasting features
• 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 so engineers can implement reliably without ambiguity
• 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 so customers can trust what they see
• 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

• 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 youre 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

Benefits and Perks

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

*please note that benefits and perks for contract positions will vary*

Culture Values

• Make Bold Bets: We choose courageous action over comfortable progress.
• Innovate with Insight: We tackle decisions with rigor and judgment - combining data experience and collective wisdom to drivepowerful outcomes.
• One Team: We collaborate across boundaries to achieve far greater impact than any of us could accomplish alone.
• Candor with Connection: We build meaningful relationships that enable honest feedback and direct conversations.
• Champion the Customer: We seek to deeply understand our customers needs ensuring their success is our north star.
• Powerful Simplicity: We find elegant solutions to complex problems making sophisticated things accessible.

Why choose Mixpanel

Were a leader in analytics with over 9000 customers and $277M invested from prominent investors: like Andreessen-Horowitz Sequoia YC and most recently Bain Capital. Mixpanels 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 youll be helping the worlds most innovative companies learn from their data so they can make better decisions.

Mixpanel is an equal opportunity employer supporting workforce diversity. At Mixpanel we are focused on things that really matterour people our customers our partnersout of a recognition that those relationships are the most valuable assets we have. 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. Weve immersed ourselves in our Culture and Values as our guiding principles for the impact we want to have and the future we are building.