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# Data Scientist

- **Company:** Lightning AI
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $245,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Big Data, BigQuery, Cloud Database, Data Centers, Python (Programming Language), SQL Databases, Google Cloud, Google Data Studio, Tools for Reporting, Looker Analytics
- **Published:** August 15, 2026
- **Apply:** https://www.dice.com/job-detail/00e84ef2-c208-4f00-98e7-bb6fe322c3fa

## About the Role

* 5+ years in a Data Science or Product Analyst role
 * Proficient using SQL to query large databases
 * Strong skills using Python to write scripts and run statistical analysis
 * Hands-on experience with BI tools (Looker or similar) and cloud data infrastructure - AWS (e.g. S3, EFS) and/or Google Cloud Platform (e.g. BigQuery, Looker Studio)
 * A strong bias for action, and the ability to make clear decisions and recommendations in the presence of uncertainty
 * Experience on a growing data team at a startup, preferred
 * Experience designing and building foundational data models from scratch, preferred

## Description

We are looking for a Data Scientist to drive informed decision-making across the company as we become the first fully-integrated neocloud for AI training. This individual will work closely with Product, Engineering, and Sales leadership, answering key questions about product usage, proactively surfacing trends, and supporting our growth in a data-driven way.

You will join the Product Team and report to our VP of Product.

This is a hybrid role based in either New York City, NY with in-office requirements of 2 days per week.
What You'll Do

 * Partner with Product, Sales, and Engineering to define questions that matter and identify product features and behaviors that drive business outcomes
 * Analyze small business and enterprise usage patterns to sharpen Ideal Customer Profiles and guide Sales prospecting priorities
 * Quantify the health of our data center business and test the impact of systematic sales, service, and operations improvements
 * Work with engineering to design, build, and maintain data pipelines that support timely and accurate analyses
 * Write SQL (and occasional scripts) to explore data, automate recurring workflows, and answer ad-hoc questions
 * Design Looker and Data Studio dashboards and reports that make findings easy for stakeholders to act on
 * Monitor trends and surface opportunities or risks early, before they show up in routine reporting
 * Help grow a data-driven culture by sharing practices and enabling teams to use analytics tools on their own


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