Staff Data Scientist

Jerry.ai•New York, NY

1d•$170,000 - $210,000•Remote

About The Position

Jerry.ai is seeking Staff Data Scientists to join their Data Science & Analytics team. This team acts as a force multiplier, driving data insights and informing decision-making across all business units. Each Data Scientist is embedded within a business unit (growth, product, AI and automation, strategic partnerships) and owns the analytical function end-to-end. The role involves defining problems, surfacing analytical insights, driving decisions, and seeing them through execution. The company is looking to expand from 5 million to 50 million customers and become a $10 billion business in the next four years, with a need for more Data Science team members to support this growth.

Requirements

6+ years of experience at a consulting firm, investment bank, or high-growth technology company.
Strong analytical skills; ability to pull, structure, and interpret data independently.
Track record of owning ambiguous problems and delivering impact.
Clear, persuasive communicator who can influence decisions at the leadership level.
First principles thinker: breaks ambiguous problems into clear hypotheses before touching data.
Analytically strong (comfortable with SQL or Python).
Direct communicator: can walk a skeptical stakeholder through a complex finding and get buy-in quickly.
Owner: acts like their name is on the door and feels responsible for fixing things, even if outside their swim lane.

Responsibilities

Sit on the central Data Science & Analytics team but be embedded in one of Jerry's core business areas (growth, product, AI and automation, strategic partnerships) and own the analytical function for that business unit end-to-end.
Define the right problems by understanding what business question an analysis is answering and what decision it will inform, and pushing back if the question is flawed.
Define metrics, build reports, run analyses, design experiments, and surface data insights that move the team's key metrics.
Bring recommendations to counterparts in product, growth, finance, or operations, explaining what's happening, why, and what the next steps should be.