Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Assist in the Defense Health Agency Revenue Cycle Operating System initiative.

• Create and implement advanced analytics in Databricks utilizing Python, SQL, Spark/PySpark, statistical techniques, and machine learning.

• Produce Databricks visualizations, SQL dashboards, AI/BI dashboards, and native visualization functionalities.

• Design interactive dashboards for DHA J-8, DHN, MTF, revenue-cycle, coding, financial, and executive stakeholders.

• Convert analytical models into visual representations that illustrate financial exposure, recovery prospects, trends, root causes, outliers, and operational priorities.

• Develop command-level RevOS SITREP dashboards featuring Healthy/At Risk/Critical indicators.

• Create drill-down analytics spanning from enterprise and DHN levels to MTF, department, provider, encounter, claim, and claim-line levels.

• Identify and assess revenue leakage and recovery potential.

• Examine encounter, documentation, coding, charge, claim, denial, adjudication, payment, and accounts-receivable data.

• Develop detection mechanisms for missing charges, delayed encounters, coding inaccuracies, claims defects, denials, underpayments, remittance issues, aged claims, and eligibility or authorization failures.

• Create models for recoverability and priority scoring.

• Generate payer-performance and denial analytics.

• Construct predictive models to identify revenue-cycle failures before they result in lost revenue or excessive Days-to-Bill.

• Establish baselines and methodologies for anomaly detection across revenue-cycle processes.

• Design financial-impact methodologies for assessing potentially recoverable revenue.

• Develop and validate standardized RevOS KPIs and analytical metrics.

• Provide support for the RevOS Revenue Opportunity Ledger.

• Develop dashboard views that link aggregate metrics to the Revenue Opportunity Ledger and actionable work queues.

• Collaborate with Data Engineers on Silver and Gold data structures.

• Enhance analytical queries and calculations for responsive, enterprise-scale dashboards.

• Validate models, KPIs, and dashboard calculations against authoritative source records.

• Create analytical data products for coding audits, payer scoring, denial management, revenue recovery, financial reconciliation, and audit remediation.

• Document the model's purpose, methodology, validation, performance, refresh frequency, limitations, and version history.

• Assist in model monitoring, validation, retraining, and ModelOps practices.

⛳️ Requirements

• 8+ years of professional experience in data science, advanced analytics, quantitative analysis, machine learning, or related fields.

• Strong hands-on experience with Databricks.

• Familiarity with Databricks native visualization and dashboard functionalities, including Databricks SQL and/or AI/BI dashboards.

• Experience in designing operational, analytical, and executive dashboards utilizing large enterprise datasets.

• Advanced proficiency in Python and SQL.

• Experience with Spark/PySpark or similar distributed-computing technologies.

• Expertise in developing predictive models, anomaly detection, classification, prioritization/scoring models, or similar analytical functionalities.

• Strong understanding of feature engineering, model validation, statistical testing, and analytical quality assurance.

• Experience handling complex financial, operational, healthcare, claims, payment, or transactional data.

• Ability to translate business and operational challenges into measurable analytical hypotheses and production-ready analytical outputs.

• Capability to communicate complex analytical results through visualizations and dashboards to both technical and non-technical audiences.

• Experience in developing KPIs that reconcile to authoritative data sources.

• Understanding of modern lakehouse and Bronze/Silver/Gold architectures.

• Ability to collaborate with Data Engineers and Architects to define data structures necessary for analytics and visualization.

• Experience in developing auditable and explainable analytical methodologies suitable for financial or regulated environments.

• Ability to work within Agile product-development and iterative delivery frameworks.

• Capability to comply with applicable DHA/DoD security, privacy, access, and data-handling protocols.

• Applicants must fulfill eligibility criteria for a U.S. Government security clearance; only U.S. Citizens are eligible for a security clearance.

• Preferred: prior experience with Advana and/or War Data Platform (WDP).

• Preferred: DoD Databricks dashboard and analytical product experience.

• Preferred: familiarity with Databricks Unity Catalog, Delta Lake, Databricks SQL, AI/BI Dashboards, MLflow, Workflows, or related functionalities.

• Preferred: experience in healthcare revenue-cycle management.

• Preferred: knowledge of 835, 837, 270/271, 276/277, and 278 healthcare payer transactions.

• Preferred: experience with MHS GENESIS, Oracle Health/Cerner Millennium, Abacus, or similar healthcare systems.

• Preferred: background in federal financial management, audit remediation, or revenue recognition.

• Preferred: certified data products, lineage, data governance, and data quality controls.

• Preferred: expertise in explainable AI/ML in regulated or government environments.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and career growth.

• Flexible work arrangements.

• Supportive and inclusive team culture.