Lead Data Scientist, Predictive Modeling & Causal Inference
New
O
OneSixData & AI Consulting
Remote/US & CanadaFull-TimeLead
Salary180,000 - 200,000 USD per year
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Job Details
- Experience
- 7+ years
- Required Skills
- PythonSQLMachine LearningSparkSoftware Engineering
Requirements
- 7+ years of hands-on experience in predictive analytics, applied statistics, or machine learning.
- Deep fluency in predictive modeling techniques spanning GLMs, econometric methods, and causal inference.
- Experience with time-series forecasting, including deep learning-based approaches.
- Strong software engineering fundamentals with experience deploying and maintaining models in production.
- Proficiency across the modern data stack (SQL, Spark, and Python).
- Excellent communication and interpersonal skills with experience in client-facing roles.
- Graduate degree (M.S. or Ph.D.) in a quantitative or behavioral field or equivalent demonstrated experience.
Responsibilities
- Design, build, and validate predictive models, from GLMs and causal/econometric methods to deep learning-based forecasting.
- Apply causal inference techniques to help stakeholders make data-driven decisions.
- Own the full lifecycle of models from exploratory analysis through deployment, monitoring, and retraining.
- Write production-grade SQL, process data in Spark, and deploy models in Python.
- Translate ambiguous business questions into well-scoped modeling problems for clients.
- Communicate technical work to both technical and non-technical stakeholders to build strategic credibility.
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