[Hiring] Lead Data Scientist @OneSix

Role Description

We're looking for a Lead Data Scientist to embed with key clients as a senior technical partner on their data science team. This is a player-coach role at the intersection of rigorous predictive modeling and production engineering.

• Design, build, and validate predictive models, from GLMs and causal/econometric methods to deep learning-based forecasting.
• Apply causal inference techniques (quasi-experimental design, uplift modeling, propensity methods, and related econometric tools).
• Own the full lifecycle of your models: from exploratory analysis and feature engineering through deployment, monitoring, and retraining.
• Work fluently across the stack, writing production-grade SQL, processing data at scale in Spark, and building and deploying models in Python.
• Partner directly with the client's data science and broader analytics team, translating ambiguous business questions into well-scoped modeling problems.
• Communicate technical work clearly to both technical and non-technical stakeholders.
• Bring engineering discipline to a production environment that is mature but imperfect.

Qualifications

• 7+ years of hands-on experience in predictive analytics, applied statistics, or machine learning.
• Deep fluency in predictive modeling techniques spanning generalized linear models, econometric methods, causal inference, and time-series forecasting.
• Strong software engineering fundamentals: experience deploying and maintaining models in production.
• Proficiency across the modern data stack (e.g., SQL, Spark, and Python).
• Excellent communication and interpersonal skills.
• A graduate degree (M.S. or Ph.D.) in a quantitative or behavioral field or equivalent demonstrated experience.
• Based in the US or Canada.

Requirements

• Experience modeling user behavior as it relates to downstream outcomes like churn, lifetime value, engagement, or propensity to convert.
• A Ph.D. in cognitive science, behavioral economics, or a similarly human-behavior-oriented quantitative field.
• Prior consulting or professional services experience, particularly in client-facing technical roles.

Benefits

• Competitive compensation.
• Company-paid medical, vision, dental, and wellness benefits for employees.
• Company-provided home office equipment.
• Flexible vacation and sick days.
• Team-oriented and supportive working environment.
• Company-sponsored events and swag.