Data Scientist, Healthcare Data Integrations

Role is only open to candidates currently located in one of the following remote-eligible states: North Carolina, Florida, Illinois, Indiana, South Carolina, Ohio, Rhode Island, Missouri, Colorado, or Virginia. This Jobot Job is hosted by: Hunter King Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume. Salary: $110,000 - $145,000 per year A bit about us: We're an AI-powered patient acquisition platform built for multi-location healthcare, dental, and veterinary practices, helping providers turn marketing spend into booked, attended appointments. Our proprietary marketing ROI (MROI) reporting closes the loop from ad click to patient visit to revenue - a level of accuracy few platforms in this space can match, and it depends entirely on the integrity of data flowing in from a wide range of EHR and practice management systems. We're now building a dedicated, high-leverage team to own that data pipeline end to end, with real room to shape the tooling, standards, and playbooks from the ground up. We're also genuinely AI-forward - tools like Claude and Cursor are part of how we work day to day, not something we discourage. Why join us? This is a rare chance to join a small, high-leverage team on day one and shape how it works - not step into a process that's already been decided for you. You'll have real ownership over the tools, standards, and playbooks this function runs on, direct access to engineering and product leadership, and the flexibility of a remote-first culture that still prioritizes genuine work-life balance and supportive leadership. We're also unapologetically AI-forward, so you'll be encouraged (not restricted) to use tools like Claude and Cursor to do your best work. And we back that up in practice: we cover 100% of health insurance premiums, offer a 4% 401(k) match with no vesting period, and every full-time salaried employee receives meaningful equity - because we believe everyone should benefit as the company grows. 100% employer-covered health insurance premiums 4% 401(k) match, no vesting period Equity (options) for every full-time salaried employee Remote-first culture Job Details **Please note: This role is only open to candidates currently located in one of the following remote-eligible states: North Carolina, Florida, Illinois, Indiana, South Carolina, Ohio, Rhode Island, Missouri, Colorado, or Virginia. Applicants outside these states will not be considered.** About us: We're an AI-powered patient acquisition platform built for multi-location healthcare, dental, and veterinary practices. We help providers turn marketing dollars into booked, attended appointments - through call tracking and classification, two-way texting, online booking capture, and marketing ROI (MROI) reporting that connects ad spend to real patient revenue. MROI is what makes our analytics genuinely differentiated: it closes the loop from a marketing click all the way to a patient who showed up and generated revenue. Keeping that reporting accurate depends entirely on the quality, completeness, and integrity of data flowing from a broad and growing set of electronic health record (EHR) and practice management (PMS) systems. That is where this team - and this role - comes in. About the team: We are standing up a dedicated Healthcare Data Integrations team to own how patient, appointment, and revenue data gets into our platform. The team is small and high-leverage — a Product Owner / Team Lead, an Integration Software Engineer, and the Data Scientist described here. Its charter spans four areas: Direct EHR/PMS integrations - designing and standing up direct connections to systems like ModMed, NextGen, Open Dental, WinOMS/Carestream, and others. Bespoke MROI audits and ingestion - profiling raw sample data from partner data sources, proving feasibility, and building the ingestion that powers MROI reporting. Aggregator program management - project-managing integrations that run through third-party data aggregators, and holding those partners accountable to data quality standards. Build vs. buy evaluation - assessing integration decisions over time based on data quality, cost, and control considerations. This is a relatively new mandate for us, so the team has unusual room to shape its own tooling, standards, and playbooks. The role: As the team's Data Scientist, you are the person who looks at a brand-new pile of healthcare data and figures out whether - and how - it can be trusted to drive revenue reporting. You will sit at the intersection of raw vendor data and our MROI product, profiling incoming data, diagnosing quality problems, defining the mappings and transformations that normalize it, and validating that what lands in our dashboards is correct. You will work hands-on every day in SQL and Python, partner closely with the Integration Software Engineer who builds the production pipelines, and act as our technical counterpart to the data analysts and engineers on the vendor and aggregator side. This is a deep individual contributor role for someone who is energized by messy, real-world healthcare data and takes pride in getting it right. Our top priorities for this role are data accuracy and security. You will be working with data used to drive millions of dollars of decisions - accuracy and transparency are essential. You will also be handling data protected under HIPAA, which must be always kept private and secure. Security is not an afterthought here, and all candidates should seriously consider the responsibility that comes with this role. What you'll do: Audit new data sources for MROI readiness. Profile EHR, PMS, and partner data-lake exports for completeness, key coverage, linkage, and revenue-reporting feasibility, then deliver a clear go / conditional-go / no-go recommendation. Diagnose and resolve data-quality blockers. Identify the specific issues that break reporting, such as missing encounter IDs, incomplete charge fields, weak patient matching, or absent creation dates, and convert them into precise requests for vendors or aggregators. Define normalization and mapping logic. Map vendor schemas to our data model and design transformations such as collapsing inconsistent, EMR-specific appointment statuses into stable FHIR-style buckets that hold up across many source systems. Partner on production ingestion. Work with the Integration Software Engineer to turn validated mappings into repeatable pipelines, including file-based and data-lake handoffs. Own ongoing data quality. Build monitoring, reconciliation, and drift-detection checks that keep MROI reporting accurate after go-live. Build the team's tooling and standards. Help turn repeated audit work into reusable tooling, templates, and eventually more automated auditing, so each successive integration is faster than the last. Support build vs. buy decisions. Help assess integration options as the program scales, weighing data quality, cost, and control against partnership and aggregator alternatives. What you'll bring: 5–7 years with production data. You have worked in data science, data engineering, data quality, or analytics engineering roles where imperfect real-world data directly affects business decisions. Strong SQL and Python. You are fluent in SQL and comfortable using Python, including pandas or equivalent tools, for profiling, validation, and transformation work every day. Healthcare data-quality judgment. You can reason about null rates, key coverage, record linkage, and downstream reporting risk, especially in patient, appointment, encounter, and charge data. Comfort with relational data modeling. You understand entity relationships and joins deeply and can reason about how dimensions and facts (patients, appointments, encounters, charges) should link. ETL and ingestion experience. You have built or closely supported pipelines involving file-based, warehouse, or data-lake handoffs such as CSV, S3, Snowflake, or similar systems. Clear written and verbal communication. You can explain a data problem precisely enough that a vendor's engineer knows exactly what to fix and summarize an audit so a product leader can make a call. Ownership and rigor. You are comfortable being accountable for whether the numbers are right and communicating issues clearly to both technical and product stakeholders. Nice to have Experience with healthcare data - EHR/PMS systems, clinical or claims/charge data, or FHIR-based models. Familiarity with specific systems in our world: ModMed, NextGen, Open Dental, WinOMS/Carestream, eClinicalWorks, AdvancedMD, or Athena. Experience working through healthcare data aggregators or middleware platforms. Working knowledge of PHI/HIPAA handling, BAAs, and secure data exchange. Snowflake and AWS (S3, IAM) familiarity, including storage-integration patterns between a partner's warehouse and your buckets. Exposure to marketing-attribution or revenue/ROI analytics. Interest in building internal tooling and pushing toward more automated, repeatable data audits. How you'll work You will report to the Healthcare Data Integrations Team Lead and work in close, day-to-day partnership with the team's Integration Software Engineer. The role also carries a strong dotted-line relationship to our Director of Engineering, who sets technical standards and helps guide the more architectural calls. You will collaborate regularly with Product, Implementation, and Customer Operations, and you will be our hands-on technical point of contact with our integration and aggregator partners. Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button. Jobot is an Equal Opportunity Employer. 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