Machinify logo

Senior Data Analyst

Machinify

Remote · USFull-time$140–170K/yrSeen todaySeen in employer's feed today

Most applications go out cold — see where you stand first. No sign-up to start.

Watch jobs like this.

At a glance

Compensation
$140–170K/yr
Location
Remote · US
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Machinify, a leading healthcare intelligence company, seeks a Senior Data Analyst to bridge client needs, internal product knowledge, and data‑driven outcomes, developing AI‑driven workflows and ensuring accurate payment‑integrity analysis across large‑scale claims data.

Skills & qualifications

RequiredNice to have

Skills

Advanced SQLSpark SQLDatabricksDelta LakeSnowflakeBigQueryLLMsAI ToolsHealthcare CodingICD-10CPTHCPCSUB-04CMS-1500Payment IntegrityValue‑Based CareETL/ELTStrong Communication

Qualifications

High School Diploma/G.E.D.5+ Years Data Analysis Experience

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off

Full job description

Experience Required

5 - 20 years

Minimum Education Required

High School Diploma/G.E.D.

Compensation

$140,000.00 - $170,000.00 / yearly

Hours Per Week

40

Number Of Positions

1

Work Schedule and Shift Requirements

First (Day)

Job Description

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 85 health plans, including many of the top 20, and representing more than 270 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.

We're seeking aSenior Data Analyst to join our Data Engineering team who brings three things together: deep healthcare domain expertise that lets you engage health plan clients directly on payment and process questions; the ability to quickly learn and work across Machinify's internal products - from data ingestion through claims adjudication; and a drive to develop and build AI-driven workflows that continuously raise the bar on what our analyst function can do. This is not a pure back-office role - you'll be the bridge between client needs, internal product knowledge, and data-driven outcomes.

What You'll Do

Collaborate with clients and internal stakeholders to understand payment integrity requirements, document process flows, and integrate analytical outputs with client workflows and downstream adjudication systems

Develop deep understanding of Machinify's internal processes and how they integrate together - from data ingestion through claims adjudication - ensuring analytical solutions are accurate, traceable, and aligned with business needs

Actively drive AI adoption: prompt and iterate with LLMs to accelerate analysis, identify processes where AI can replace manual workflows, and contribute to AI-assisted pipeline development

Write and maintain complex analytical SQL against large-scale claims datasets: window functions, CTEs, multi-table joins, query optimization, and production-quality logic that runs reliably at scale

Identify and build AI-driven automation workflows that replace or accelerate manual analytical processes - moving from one-off prompts to repeatable, team-shareable tooling

Design and implement data transformations that convert raw medical and institutional claims into canonical models, applying healthcare coding standards (ICD-10, CPT, HCPCS, UB-04, CMS-1500) throughout

Drive payment integrity analysis - identify overpayment patterns, coordination of benefits issues, and billing edit opportunities by applying deep knowledge of payer policy, CMS regulations, and provider reimbursement methodologies

Conduct data quality audits and build monitoring frameworks that surface anomalies before they reach production

Support onboarding of new client data feeds, ensuring smooth integration with minimal disruption

Partner with engineers, clinical staff, and product managers to translate complex healthcare requirements into data solutions

Mentor analysts and engineers on healthcare domain questions - serving as the go-to SME on coding, claims adjudication, and payer policy

Document transformation logic, data lineage, and analytical methodologies to support knowledge transfer and audit readiness

What You Bring

5+ years of data analysis experience and working directly with healthcare claims data

Deep knowledge of medical claim types (professional and institutional), coding systems (ICD-10-CM/PCS, CPT, HCPCS), and standard form formats (UB-04, CMS-1500)

Demonstrated experience using LLMs or AI tools to accelerate analytical work - not as a novelty, but as a repeatable part of your workflow

Expert-level SQL: complex analytical queries, window functions, CTEs, performance tuning against datasets of hundreds of millions of rows

Hands-on payment integrity experience: overpayment detection, COB, billing edits, or claim editing logic

Familiarity with CMS regulations and commercial payer guidelines as they apply to claims adjudication and payment policy

Strong communicator - able to discuss healthcare process and payment logic directly with health plan clients and non-technical stakeholders

Ability to translate ambiguous business and clinical requirements into precise, well-documented data logic

Working knowledge of provider reimbursement methodologies - MS-DRG/APR-DRG pricing, fee schedules, per diem, and capitation

Proficiency with Spark SQL or a comparable distributed query engine - writing and optimizing queries against large-scale data environments is a daily expectation

Experience with Databricks or a cloud data lakehouse (Delta Lake, Snowflake, BigQuery)

Background in ETL/ELT pipeline development or close collaboration with data engineers on pipeline design

Exposure to value-based care arrangements or risk adjustment (HCC coding, RADV)

Prior experience at a health plan, payment integrity vendor, or healthcare analytics firm

What We Offer

Workfrom anywhere in the US!Machinifyis digital-first.

Full Medical/Dental/Vision for employees & their families

Flexible and trusting environment whereyou'llfeel empowered to do your best work

Unlimited FTO

Competitive salary, equity, 401(k) including employer match

The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. The base salary range for this role is $140,000-$170,000. We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks.

Equal Employment Opportunity at Machinify

We are committed to equal employment opportunity regardless of r ace, color, ancestry, r eligion, s ex, national origin, s exual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at:https://www.machinify.com/candidate-privacy-notice/

Equal Opportunity Employer

Veteran Friendly Employer

Job Type

Full time

Benefits Offered

Not specified

Veteran Preference

No

Place of Work

On-site

Requisition ID

4333221009

Similar jobs, posted recently

Open roles like this one, listed in the last 30 days.

You've read the whole posting — now see how you match it.