Data Scientist
6 - 10 years
New York, NY
Full-time
Hybrid
1 month ago
About the role
About The Role
The role designs statistical and machine learning solutions that translate messy, high-dimensional data into clear business insight.
The work spans the full spectrum: you will write production SQL one day and design a causal inference study the next. Scientific rigor and business impact matter in equal measure.
Key Responsibilities
What We Are Looking For
Location
New York City (Hybrid)
The role designs statistical and machine learning solutions that translate messy, high-dimensional data into clear business insight.
The work spans the full spectrum: you will write production SQL one day and design a causal inference study the next. Scientific rigor and business impact matter in equal measure.
Key Responsibilities
- Develop, validate, and deploy predictive models (regression, classification, clustering, time-series) for real business decisions across client verticals
- Design and analyze A/B tests and quasi-experimental studies with appropriate statistical rigor; communicate results to business and executive stakeholders
- Write efficient, well-documented SQL and Python analytical code; maintain model pipelines with appropriate quality monitoring
- Collaborate with data engineers on feature engineering, data quality, and pipeline reliability for training and serving
- Conduct exploratory data analysis to surface non-obvious patterns and generate hypotheses that drive product roadmap decisions
- Present findings clearly in written reports, dashboards, and executive presentations - translating statistical nuance into confident recommendations
- Contribute to team knowledge-sharing; stay current on methodological advances relevant to our problem spaces
What We Are Looking For
- 2–5 years of data science experience with demonstrable production impact (not just analyses - decisions that changed what someone did)
- Strong Python: pandas, scikit-learn, statsmodels; SQL at the level of writing and optimizing complex analytical queries without help
- Deep statistical foundations: hypothesis testing, regression modeling, experimental design, probability distributions
- Experience with at least one cloud data warehouse: Snowflake, BigQuery, or Redshift
- Clear, structured written and verbal communication - you can make a p-value meaningful to a CFO
- MS or BS in Statistics, Computer Science, Mathematics, Economics, or a closely related quantitative field
- Bonus: causal inference methods (DiD, synthetic control, IV), ML model deployment experience, Spark, or NLP
Location
New York City (Hybrid)
- San Francisco
- Seattle
- Boston
Skills
Staffing and RecruitingCivil EngineeringResearch