Senior Data Scientist

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $140.4k - $185.6k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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LMI

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1961

📦 Logistics

🏥 Healthcare

🎖️ Defense

Logistics • Healthcare • Defense

LMI is a forward-thinking company that focuses on reimagining the path from insight to outcome through innovative solutions in various sectors, including applied AI and digital health. They provide advanced analytics, engineering support, and performance optimization across defense, health, and civilian markets, with a strong commitment to enhancing mission effectiveness for government clients. With a focus on collaboration and research, LMI aims to drive positive change through its diverse capabilities and partnerships.

📋 Description

• Support the Defense Health Agency Revenue Cycle Operating System initiative • Design and develop advanced analytics within Databricks using Python, SQL, Spark/PySpark, statistical methods, and machine-learning techniques • Develop Databricks visualizations, Databricks SQL dashboards, AI/BI dashboards, and native visualization capabilities • Create interactive dashboards for DHA J-8, DHN, MTF, revenue-cycle, coding, financial, and executive users • Translate analytical models into visualizations showing financial exposure, recovery opportunity, trends, root causes, outliers, and recommended operational priorities • Develop command-level RevOS SITREP dashboards using Healthy/At Risk/Critical indicators across Front, Middle, and Back Office revenue-cycle processes • Develop drill-down analytics from enterprise and DHN levels through MTF, department, provider, encounter, claim, and claim-line levels • Design analytical models identifying and quantifying revenue leakage and recovery opportunities • Analyze encounter, documentation, coding, charge, claim, denial, adjudication, payment, and accounts-receivable data • Develop detection logic for missing or incomplete charges, uncoded or delayed encounters, coding errors, claims-readiness defects, denied or rejected claims, underpayments, unmatched remittances, aged claims and receivables, and eligibility or authorization failures • Develop recoverability and priority-scoring models • Develop payer-performance and denial analytics • Build predictive models identifying revenue-cycle failures before lost revenue or excessive Days-to-Bill • Establish baselines and anomaly-detection methodologies • Design financial-impact methodologies estimating potentially recoverable revenue • Develop and validate standardized RevOS KPIs and analytical measures • Support the RevOS Revenue Opportunity Ledger • Create dashboard views connecting aggregate metrics to the Revenue Opportunity Ledger and actionable work queues • Partner with Data Engineers to ensure Silver and Gold structures support analytics and dashboard performance • Optimize analytical queries and calculations for responsive enterprise-scale visualization • Validate models, KPIs, and dashboard calculations against authoritative source records • Develop analytical data products for coding audit, payer scoring, denial management, revenue recovery, financial reconciliation, and audit remediation • Document model purpose, features, methodology, validation, performance, refresh cadence, limitations, and version history • Support model monitoring, validation, retraining, and ModelOps practices

🎯 Requirements

• 8+ years of professional experience in data science, advanced analytics, quantitative analysis, machine learning, or related disciplines • Strong hands-on experience with Databricks • Demonstrated ability to use Databricks native visualization and dashboard capabilities, including Databricks SQL and/or AI/BI dashboards • Experience designing operational, analytical, and executive dashboards based on large enterprise datasets • Advanced proficiency with Python and SQL • Experience with Spark/PySpark or comparable distributed-computing technologies • Experience developing predictive models, anomaly detection, classification, prioritization/scoring models, or similar analytical capabilities • Strong understanding of feature engineering, model validation, statistical testing, and analytical quality assurance • Experience working with complex financial, operational, healthcare, claims, payment, or transactional data • Ability to translate business and operational problems into measurable analytical hypotheses and production-ready analytical products • Strong ability to communicate complex analytical findings through visualizations and dashboards to both technical and non-technical users • Experience developing KPIs that reconcile to authoritative data sources • Understanding of modern lakehouse and Bronze/Silver/Gold architectures • Ability to work with Data Engineers and Architects to define data structures required for analytics and visualization • Experience developing auditable and explainable analytical methodologies appropriate for financial or regulated environments • Ability to operate within Agile product-development and iterative delivery environments • Ability to meet applicable DHA/DoD security, privacy, access, and data-handling requirements • Applicants must meet eligibility requirements for a U.S. Government security clearance • Only US Citizens are eligible for a security clearance • LMI will only consider applicants with security clearances or applicants who are eligible for security clearances • Preferred: Prior experience with Advana and/or the current War Data Platform (WDP) • Preferred: Experience developing dashboards and analytical products within a DoD Databricks environment • Preferred: Experience with Databricks Unity Catalog, Delta Lake, Databricks SQL, AI/BI Dashboards, MLflow, Workflows, or related capabilities • Preferred: Healthcare revenue-cycle experience, including coding, claims, charge capture, denials, AR, remittance, payer reimbursement, and underpayment analysis • Preferred: Familiarity with healthcare payer transaction data such as 835, 837, 270/271, 276/277, and 278 transactions • Preferred: Experience with MHS GENESIS, Oracle Health/Cerner Millennium, Abacus, or similar healthcare systems • Preferred: Experience supporting federal financial management, audit remediation, or revenue-recognition initiatives • Preferred: Familiarity with certified data products, lineage, data governance, and data-quality controls • Preferred: Experience developing explainable AI/ML capabilities in regulated or Government environments