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# Data Scientist

- **Company:** AI BUILDS LLC
- **Location:** New York, NY, United States
- **Salary:** $150,000.0 - $300,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Amazon Web Services, Monitoring of Systems, Python (Programming Language), Machine Learning, Workflow Management Systems, Feature Engineering, Evaluation Pipelines, Large Language Models, Apache Spark, Model Validation, Pandas, Scikit Learn
- **Published:** October 27, 2026
- **Apply:** https://www.builtincolorado.com/job/data-scientist/11889852?handler=ApplyRedirect

## About the Role

* Experience developing and validating models on real, messy data - through internships, prior roles, or substantive project work.

 * Solid foundation in statistics and machine learning: regression, time series, tree-based methods, experimental design.

 * Strong Python (pandas, scikit-learn, and the surrounding ecosystem) and strong SQL.

 * Curiosity about the business problem behind the data, not just the modeling technique.

 * Clear communication - you can explain what you did, why, and what it means, to someone who doesn't do this for a living.

 * Strong problem-solving skills, adaptability, and a "hacker" mentality.

 * Eagerness to learn quickly in a startup environment.

Nice to have

 * Exposure to CPG, retail, or consumer brand data.

 * Experience with Spark, cloud platforms (AWS or similar), or orchestration tools.

 * Familiarity with LLMs and their practical use in analytical workflows.

## Description

As a Data Scientist, you will build the models that turn customer data into decisions - forecasting, optimization, measurement, and the analysis that tells us whether any of it is working.

You'll work across the full lifecycle: understanding a business problem, exploring the data, developing and validating models, and partnering with engineers to get them into production. You'll also work directly with customer data and customer-facing teams, which means your analysis needs to hold up under scrutiny from people whose decisions depend on it.

This role is a strong fit for someone earlier in their career who wants real ownership quickly. You'll get direct mentorship from our Co-Founder & CAIO and senior engineers, and the scope to grow fast.

RESPONSIBILITIES

Modeling & Analysis

 * Develop, validate, and iterate on models for forecasting, optimization, anomaly detection, and measurement.

 * Perform exploratory analysis on complex customer datasets to surface patterns worth acting on.

 * Design and analyze experiments; build the measurement approaches that quantify business impact.

 * Establish rigorous validation practices - backtesting, holdouts, and honest error analysis.

Production & Collaboration

 * Partner with ML and data engineers to move models from notebook to production.

 * Contribute to feature engineering, evaluation pipelines, and model monitoring.

 * Write clean, reproducible Python that other people can read and build on.

Business Impact

 * Translate business questions into analytical problems, and analytical results back into recommendations.

 * Communicate findings clearly to internal teams and customers, including non-technical audiences.

 * Follow deployed models into the real world and help make sure they're delivering what we promised.