layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Senior Data Scientist, AI Product Insights at Mixpanel | LAYIQ

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
We're Looking For Someone Who Has
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
Bonus Points For 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

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 drive powerful 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?
We’re a leader in analytics with over 29,000 customers and $277M invested 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.
Mixpanel is an equal opportunity employer supporting workforce diversity. At Mixpanel, we are focused on things that really matter—our people, our customers, our partners—out 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. We’ve immersed ourselves in our Culture and Values as our guiding principles for the impact we want to have and the future we are building.

Senior Data Scientist, AI Product Insights

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