Data Scientist

Sciemo is building data products that help customers turn customer data into real decisions across forecasting, optimization, and measurement. As a Data Scientist, you’ll develop and validate models, then work with engineering teams to bring them from research into production and demonstrate measurable impact to customers. This hybrid role is based in New York City, with flexibility for qualified remote U.S. candidates who can travel to the NYC office monthly.

What you’ll do

• Develop, validate, and iterate on models for forecasting, optimization, anomaly detection, and measurement.
• Run exploratory analysis on complex customer datasets to surface patterns worth acting on.
• Design and analyze experiments, building measurement approaches that quantify business impact.
• Set up rigorous validation practices, including backtesting, holdouts, and honest error analysis.
• Collaborate with ML and data engineers to move models from notebooks to production.
• Support feature engineering, evaluation pipelines, and model monitoring.
• Write clean, reproducible Python that others can read and improve.
• Translate business questions into analytical problems, and return analytical results as recommendations.
• Communicate findings clearly to internal teams and customers, including non-technical audiences.
• Follow deployed models in the real world to help ensure they deliver what was promised.

What we’re looking for

• Experience developing and validating models on real, messy data through internships, prior roles, or substantive project work.
• A strong foundation in statistics and machine learning, including regression, time series, tree-based methods, and experimental design.
• Strong Python (with pandas, scikit-learn, and related tools) and strong SQL.
• Curiosity about the business problem behind the data, not just the modeling technique.
• Clear communication skills, with the ability to explain what you did, why, and what it means to non-specialists.
• Strong problem-solving skills, adaptability, and a hacker mentality.
• Eagerness to learn quickly in a startup environment.

Tools you’ll use

Python, pandas, scikit-learn, SQL, Spark, AWS, and LLMs.

Compensation and location

$150,000 - $300,000 per year. Hybrid role in New York, NY. Remote U.S. candidates are welcome if you can travel monthly to the NYC office.

Benefits

Check out our one pager!

Nice to have

• Exposure to CPG, retail, or consumer brand data.
• Experience with Spark, AWS or similar cloud platforms, or orchestration tools.
• Familiarity with LLMs and their practical use in analytical workflows.