Staff Data Scientist | ML

Machinify • Palo Alto, CA

9d

About The Position

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 60 health plans, including many of the top 20, and representing more than 160 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
Machinify builds machine learning models for some of the largest health plans in the country to identify nearly $1B in erroneous healthcare payments. Our customers receive tens of millions of claims each year, many of which are billed with mistakes or fraud. Our production models detect and stop those errors on a daily basis, resulting in measurable healthcare savings that significantly outperform industry standards. Machinify has already had a huge impact as a small company, and we are growing quickly!
We are looking for a Staff Data Scientist | ML for our "Pay" team (claims payments product) to advance our models further. In addition to building best-in-class models, this person will create technical frameworks and tools to help the team achieve greater scale and improved business outcomes.

Requirements

• Proven track record of hands-on data science impact on real-world problems, not just research or dashboards.
• Strong proficiency in SQL, with experience working directly on complex, large-scale datasets.
• Experience building, shipping, or supporting production ML systems, preferably some exposure to LLM-based products or workflows.
• Ability to independently scope ambiguous problems, identify the right data and methods, and drive work to completion.
• Strong communication skills, with the ability to explain complex analyses and models to non-technical stakeholders.

Responsibilities

• Solve real business problems with data: Own end-to-end data science work, from problem framing and data exploration to modeling, validation, and production impact.
• Lead high-impact initiatives: Drive complex efforts such as vendor leakage detection and prevention, delivering measurable revenue or cost improvements.
• Innovate on methods and approaches: Go beyond standard analyses by developing new metrics, models, or workflows when existing approaches fall short.
• Build and productionize models: Design, build, and support production ML or LLM-powered solutions in collaboration with engineering and product partners.
• Work deeply with data: Use SQL fluently to explore large datasets, build reliable data assets, and validate results.
• Influence cross-functionally: Partner with Product, Engineering, Finance, and Operations to align on goals, tradeoffs, and execution plans.
• Set technical direction (especially at L7): Raise the bar for data science quality, scalability, and impact across the organization through mentorship, design reviews, and technical leadership.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees