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# Data Science - WFH

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $175,000.0 - $210,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Data Analysis, BigQuery, Mobile Application Software, Python (Programming Language), Machine Learning, Automation of Marketing, Multivariate Testing, Natural Language Processing, Recommender Systems, Standard Sql, DataOps, Search Technologies, SQL Databases, Usage Analysis, Reinforcement Learning, Claude Code, Data Pipelines
- **Published:** October 9, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pq01ue7ylv

## About the Role

* PhD or advanced degree in Data Science, Economics, Business Analytics, Mathematics, Statistics, or a similar quantitative field, or equivalent experience.

 * 7+ years of experience in data science and machine learning, with a strong focus on customer behavior, product analytics, and marketing-focused problems.

 * 5+ years of experience leading a team of data scientists.

 * Experience leading product and funnel analytics across web and mobile platforms.

 * Strong foundation in causal inference, survival analysis, and time series analysis.

 * Strong proficiency in Python and SQL for data analysis and model development.

 * Familiarity with Claude Code/Codex and their reliable use cases and limitations within data science workflows.

 * Strong strategic and operational capabilities.

 * Excellent leadership and communication skills.

 * Ability to communicate complex analytical findings clearly to non-technical stakeholders.

 * Ability to drive adoption of new data science methods and technologies.

## Preferred Qualifications

 * Experience with large-scale search and recommendation systems in media, e-commerce, or advertising.

 * Experience with large-scale analytics platforms such as BigQuery.

 * Exposure to reinforcement learning or bandit approaches for personalization or offer optimization.

 * Experience with advanced experimentation techniques, including multivariate testing, factorial designs, and CUPED.

 * Experience with Bayesian statistical methods for inference and decision-making under uncertainty.

 * Experience with forecasting models and advanced lifecycle or retention modeling.

 * Applied NLP experience in content classification, semantic search, or audience understanding.

 * Experience with mobile app personalization and customer lifecycle optimization.

 * Ability and willingness to travel periodically or quarterly for team meetings and events.

## Skills & Competencies

 * Data Science Leadership

 * Machine Learning

 * Customer Intelligence

 * Customer Behavior Analytics

 * Product Analytics

 * Marketing Analytics

 * Personalization

 * Customer Segmentation

 * Customer Acquisition

 * Customer Engagement

 * Customer Retention

 * Lifetime Value Modeling

 * Causal Inference

 * Survival Analysis

 * Time Series Analysis

 * Experimentation and A/B Testing

 * Bayesian Statistics

 * Forecasting

 * Recommendation Systems

 * Search Systems

 * Natural Language Processing (NLP)

 * Python

 * SQL

 * BigQuery

 * Data Science Strategy

 * Statistical Modeling

 * Analytics

 * Cross-Functional Collaboration

 * Executive and Stakeholder Communication

 * Team Leadership

## Education & Experience

Education: PhD or advanced degree in Data Science, Economics, Business Analytics, Mathematics, Statistics, or a similar quantitative field, or equivalent experience.

Experience: 7+ years of data science and machine learning experience focused on customer behavior, product analytics, and marketing problems, including 5+ years leading a team of data scientists.

## Work Arrangement & Schedule

 * Work Arrangement: Fully Remote

 * In-Office Requirement: No regular in-office requirement; periodic office attendance may be required for team meetings or similar events.

 * Travel: Approximately 5%; periodic or quarterly travel for team meetings/events is preferred but flexible based on candidate needs.

## Description

People Inc., America's largest print and digital publisher, is seeking a Director of Data Science to lead customer intelligence and personalization across its entertainment brands. This role will develop a deeper understanding of customer behavior across product engagement, marketing response, and lifecycle activity, translating data into actionable insights that improve products, customer experiences, and business growth.

The Director will lead a team of data scientists and partner closely with Product, Marketing, Editorial, Data Operations, and Engineering teams. The role will apply statistical modeling and machine learning to customer segmentation, acquisition, engagement, retention, lifetime value, personalization, automated marketing, attribution, experimentation, and lifecycle optimization, with a particular focus on mobile app experiences.

## Key Responsibilities

 * Lead customer intelligence and personalization initiatives across entertainment brands.

 * Lead and develop a team of data scientists.

 * Build analytics and models to understand customer engagement, marketing response, and lifecycle behavior.

 * Lead product and funnel analytics across web and mobile platforms.

 * Apply statistical modeling and machine learning to customer and marketing challenges.

 * Develop and oversee models supporting customer segmentation, acquisition, engagement, retention, and lifetime value.

 * Support personalization, automated marketing, attribution, experimentation, and lifecycle optimization across mobile apps, newsletters, and other customer touchpoints.

 * Partner with Product, Marketing, and Editorial teams to translate data into actionable insights and measurable business impact.

 * Collaborate with Data Operations and Engineering to ensure models, measurement systems, and insights can scale effectively.

 * Lead end-to-end data science projects from problem framing through deployment and impact measurement.

 * Apply causal inference, survival analysis, and time series analysis to marketing and customer behavior problems.

 * Drive adoption of new data science methods and technologies.

 * Communicate complex analyses and recommendations clearly to non-technical marketing and business stakeholders.