Staff Data Scientist, ML — Production Pay AI (Remote)

Machinify; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Medical/Dental/Vision

401(k) with company match

Tuition reimbursement

Unlimited PTO

Work from anywhere in the US

Job summary

Machinify is seeking a Staff Data Scientist for the Pay team to advance machine learning models for claims payments. You will own end-to-end data science work, build production ML or LLM-powered solutions, and collaborate with engineering, product, and finance to align on goals and drive business impact.

The role emphasizes scaling models, developing new metrics, and mentoring others to raise technical quality and impact across the organization.

Qualifications

• Proven track record of hands-on data science impact on real-world problems.
• Strong proficiency in SQL, with experience working on large-scale datasets.
• Experience building or supporting production ML systems, exposure to LLM-based workflows.
• Ability to independently scope ambiguous problems and drive to completion.
• Strong communication skills to explain analyses to non-technical stakeholders.

Responsibilities

• Own end-to-end data science work from problem framing to production impact.
• Lead high-impact initiatives delivering measurable revenue or cost improvements.
• Innovate with new metrics, models, or workflows when needed.
• Build and productionize models with engineering and product partners.
• Collaborate across teams to align goals and execution plans.

Skills

SQL proficiency

Production ML systems

LLM-based workflows

Problem scoping

Communication skills

Job description

Machinify is seeking a Staff Data Scientist for the Pay team to advance machine learning models for claims payments. You will own end-to-end data science work, build production ML or LLM-powered solutions, and collaborate with engineering, product, and finance to align on goals and drive business impact.

The role emphasizes scaling models, developing new metrics, and mentoring others to raise technical quality and impact across the organization.