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Data Science Engineer Revenue Cycle Management (RCM)

Position Summary

seeking a Data Science Engineer to build and operationalize data

products that improve healthcare revenue cycle performance. This role will work with data

from the company s warehouse and business applications to develop trusted analytics,

predictive models, and decision-support tools for RCM teams. The successful candidate

combines robust data engineering skills with applied data science expertise and can

translate operational questions into reliable, measurable solutions.

Microsoft Fabric engineering experience is a must. Most data for this role will come from

nimble s new data warehouse, so the engineer must be able to work effectively with Fabric-

based data pipelines, lakehouse/warehouse patterns, transformations, and analytics

workflows.

Key Responsibilities

Build, maintain, and optimize data ingestion and transformation pipelines in

Microsoft Fabric.

Develop and support lakehouse and warehouse data structures, curated data

models, and reusable datasets for analytics and data science.

Integrate data from the enterprise warehouse and relevant RCM, financial,

operational, and third-party sources, subject to approved access and data

governance.

Profile, validate, reconcile, and document data; investigate quality issues and work

with source systems and business teams to resolve them.

Apply statistical analysis and machine-learning methods to practical RCM problems,

such as denial patterns, accounts receivable prioritization, payment and claims

trends, workflow forecasting, and operational capacity planning.

Develop reproducible feature engineering, model training, evaluation, and scoring

workflows; select metrics that reflect business outcomes and model risk.

Deploy, monitor, and maintain data products and models in collaboration with data

engineering, analytics, applications, and business teams.

Create clear visualizations, dashboards,



and written findings that help RCM

stakeholders understand performance, drivers, and recommended actions.

Partner with subject-matter experts to define use cases, success measures,

requirements, and appropriate human review for decision-support outputs.

Follow data governance, privacy, security, and responsible AI practices, especially

when working with sensitive healthcare or financial information.

Maintain technical documentation, lineage, testing, and support procedures for

pipelines, datasets, and models.

Required Qualifications

Bachelor s degree in Data Science, Computer Science, Statistics, Engineering,

Mathematics, or a related field; equivalent practical experience may be considered.

Demonstrated hands-on experience engineering data solutions in Microsoft Fabric.

This is a required qualification, not a preferred skill.

Strong SQL skills and experience with Python for data preparation, analysis, and

model development.

Experience building production-quality data pipelines, transformations, and

analytical data models.

Working knowledge of data warehousing, dimensional modeling, data quality

testing, and pipeline monitoring.

Experience applying statistical or machine-learning techniques to real-world business

problems, including model evaluation and communication limitations.

Ability to explain technical findings to both technical teams and business

stakeholders.

Strong problem-solving, documentation, collaboration, and prioritization skills.

Preferred Qualifications

Experience in healthcare revenue cycle management, medical billing, claims, denials,





payment posting, coding, or accounts receivable.

Familiarity with healthcare data and relevant privacy and security expectations.

Experience with Power BI and semantic models, including preparing governed

datasets for reporting.

Experience with source control, automated testing, CI/CD, and production

monitoring for data solutions.

Experience with model deployment, monitoring, drift evaluation, and responsible

use of predictive outputs.

Familiarity with Microsoft Azure data services and integration patterns that

complement Microsoft Fabric.

Success Measures

Reliable, well-documented Fabric pipelines and curated datasets that meet agreed

freshness and quality expectations.

Reduced time spent on manual data preparation and reconciliation for RCM

reporting and analysis.

Analytics and models that are adopted by stakeholders and demonstrate measurable

operational value.

Clear ownership, monitoring, and support processes for production of data products.

Consistent adherence to data governance, privacy, security, and responsible AI

requirements.

Working Relationships

The role works closely with data engineering, analytics, business intelligence, IT, application

teams, and RCM operational stakeholders. It collaborates with subject-matter experts to

ensure data products address real workflows and produce interpretable, actionable results.

Position Details

Department: Data & Analytics / Data Science

Reports to: Eric Pidgeon, Director Data & AI

Location: Hyderabad

Employment type: FULL TIME

This job description describes the role s general scope and is not an exhaustive list of duties.

Responsibilities and requirements may be adjusted based on business needs.

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Warm Regards

Durva Ingle

Senior Consultant-Talent Acquisition

+91- (phone hidden)

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📌 Data Science Engineer – Revenue Cycle Management (RCM) (India)
🏢 CIEL HR
📍 India