Founding Principal Data Scientist — Hybrid NYC, High Impact

Harnham; New York (NY); Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Salary up to 200k

Annual bonus

Founding DS role

Roadmap ownership

Leadership visibility

Hybrid NYC on-site

Job summary

Harnham, a leading data and AI advisory, is hiring a Principal Data Scientist as a founding member in NYC. This hands-on leadership role offers ownership of complex end-to-end DS and ML initiatives, partnering with senior stakeholders to define a scalable data science capability.

You'll shape the roadmap, build models from concept to deployment, and drive value across commercial and operational decisions in a hybrid NYC-based environment (3 days on-site).

Qualifications

• Significant professional experience delivering Data Science and ML solutions in commercial environments.
• Advanced Python and SQL skills.
• Strong experience building predictive models from concept to deployment.
• Ability to translate ambiguous business problems into analytical approaches.

Responsibilities

• Lead end-to-end Data Science and ML projects from discovery to deployment.
• Identify high-value opportunities for predictive analytics across the business.
• Build models that influence commercial and operational decisions.
• Partner with senior stakeholders to translate business problems into technical strategies.
• Help establish best practices around modeling and deployment.
• Influence the future DS roadmap, tooling, and architecture.
• Hands-on coding with Python, SQL, and modern DS tooling.

Skills

Python

SQL

Machine Learning

Data Science

Tools

Python

SQL

Job description

Harnham, a leading data and AI advisory, is hiring a Principal Data Scientist as a founding member in NYC. This hands-on leadership role offers ownership of complex end-to-end DS and ML initiatives, partnering with senior stakeholders to define a scalable data science capability.

You'll shape the roadmap, build models from concept to deployment, and drive value across commercial and operational decisions in a hybrid NYC-based environment (3 days on-site).