Lead Data Scientist, Predictive Modeling, Causal Inference

🕒 August 19

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

💵 $180k - $200k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 4%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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OneSix

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2013

💼 Consulting

🏥 Healthcare

🤖 Artificial Intelligence

Consulting • Healthcare • Artificial Intelligence

OneSix is a company that harnesses the power of data and AI to drive practical business outcomes across various sectors. With expertise in Data & AI Strategy, Data Engineering, Data Analytics, and AI & Machine Learning, they provide end-to-end solutions tailored to meet the unique challenges in industries such as Financial Services and Healthcare. Their skilled team of Data Engineers, Data Scientists, and AI/ML Engineers work closely with clients to unlock data potential and enhance operational efficiency.

📋 Description

• Design, build, and validate predictive models, including GLMs, causal/econometric methods, and deep learning-based forecasting • Apply causal inference techniques such as quasi-experimental design, uplift modeling, propensity methods, and related econometric tools • Own the full model lifecycle from exploratory analysis and feature engineering through deployment, monitoring, and retraining in production • Write production-grade SQL, process data at scale in Spark, and build and deploy models in Python • Partner with client data science and analytics teams to translate ambiguous business questions into scoped modeling problems • Communicate technical work to technical and non-technical stakeholders and inform strategic decisions • Improve reliability and maintainability in mature production environments

🎯 Requirements

• 7+ years of hands-on experience in predictive analytics, applied statistics, or machine learning, with a track record of taking models from concept into production • Deep fluency in generalized linear models, econometric methods, causal inference, and time-series forecasting, including deep learning-based forecasting approaches • Strong software engineering fundamentals, including production model deployment and maintenance, code quality, testing, and monitoring • Proficiency in SQL, Spark, and Python • Excellent communication and interpersonal skills; strong client/stakeholder capability • A graduate degree (M.S. or Ph.D.) in a quantitative or behavioral field (statistics, economics, computer science, cognitive science, or a related discipline) or equivalent demonstrated experience • Based in the US or Canada

🏖️ Benefits

• 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