Senior Data Scientist

🕒 September 9

🇺🇸 United States – Remote

💵 $140.4k - $185.6k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• 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 related native visualization capabilities for RevOS performance • 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 • 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 charges, delayed encounters, coding errors, claims-readiness defects, denied claims, underpayments, unposted remittances, aged 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 across revenue-cycle processes • Design financial-impact methodologies estimating potentially recoverable revenue while separating analytical estimates from official accounting determinations • 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, visualization, 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 • 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 preferred, including coding, claims, charge capture, denials, AR, remittance, payer reimbursement, and underpayment analysis • 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 preferred • Applicants must meet eligibility requirements for a U.S. Government security clearance; only U.S. Citizens are eligible for a security clearance • LMI will only consider applicants with security clearances or applicants who are eligible for security clearances