Data Scientist

• Lead exploratory analysis of claims paid data to identify utilization patterns, anomalies, and potential overpaid or inappropriate claims
• Apply knowledge of CMS rules, contract interpretation, reimbursement, and workflows to guide data mining and investigative efforts
• Reverse engineer claims outcomes to understand root causes of payment issues and system behaviors
• Translate operational and claims insights into use cases, concepts, and solution ideas for analytics and product teams
• Partner with analytics, product, and strategy teams to align solutions with real-world claims operations
• Validate data-driven findings against practical claims and payment realities
• Communicate insights, risks, and opportunities to technical and non-technical stakeholders
• Support refinement and scaling of claims monitoring and overpayment detection capabilities

Manager – Data Mining, Exploratory Intelligence

Auditor

• Conduct comprehensive reviews of inpatient medical records to validate ICD-10-CM/PCS codes and DRG classifications
• Ensure compliance with IPPS methodology, CMS guidelines, and official coding rules
• Verify diagnoses, procedures, POA indicators, and discharge disposition
• Identify documentation gaps and collaborate with clinical teams to obtain clarifications
• Mentor, coach, and support coding staff on complex DRG and inpatient coding scenarios
• Deliver feedback and ongoing education to coders and Clinical Documentation Improvement specialists
• Perform routine coding quality audits and recommend corrective actions
• Analyze audit findings and prepare detailed reports
• Stay updated on regulatory changes, payer guidelines, and industry best practices
• Participate in cross-functional meetings with coding, CDI, compliance, and operations teams
• Follow SOPs, complete audits with quality, achieve quality and production targets, and follow project protocols
• Escalate issues, identify trends, update productivity and clarification logs daily, and promptly answer manager emails
• Ensure team compliance with HIPAA and OIG requirements

Senior Executive – Coding Auditor

• Follow every aspect of SOP without fail
• Complete received audits with quality
• Achieve quality and production targets
• Follow project-related protocols and instructions
• Escalate issues and identify trends
• Update productivity, clarification, and other applicable logs daily
• Check with Manager/TL for clarifications
• Answer all Manager emails promptly
• Apply problem-solving skills
• Ensure entire team compliance with HIPAA and OIG requirements

Senior Coding Auditor

Manager

• Engage with clients to identify key business problems and improvement opportunities
• Provide day-to-day project management and execution of analytics products and services
• Use statistical software and tools to perform risk analytics
• Develop machine learning models using Python/R/SAS to create risk/fraud scores for commercial and consumer credit underwriting
• Create statistically sound experiments using design of experiments (DOE) methods
• Develop automated KPI dashboards using Visual Basic and Tableau
• Create, manage, and manipulate analytical datasets using Teradata, Hive, and MySQL
• Use forecasting methods to predict future financial performance of portfolios
• Design risk management strategies across the customer credit lifecycle
• Lead performance appraisals of reporting team members
• Work with senior client management to execute analytical solutions, meet regulatory goals, and outline strategy roadmaps
• Position may work at various and unanticipated worksites throughout the United States; telecommuting permitted

Engagement Manager

Data Engineer

• Build and maintain large-scale data pipelines and platforms
• Use Python and PySpark for data engineering tasks
• Work with AWS services for data processing and storage, including S3, Glue, Athena, Lambda, and Redshift
• Apply problem-solving and performance optimization techniques

• Design and develop new machine learning and Natural Language Processing (NLP) models
• Design, train, and implement ML and deep learning architectures
• Establish evaluation metrics, analyze performance, brainstorm future steps and expansion, and perform exploratory data analysis and data visualization
• Build multi-feature ML classification models for various clinical programs and clients
• Design and develop NLP models for unstructured medical records to improve in-house algorithms
• Oversee delivery of results with analytic insights, interpretations, and recommendations
• Review analytic deliverables, identify and resolve data issues, and recommend investigations
• Design, develop, evolve, and implement processes and procedures ensuring compliance with governance policies
• Propose state-of-the-art technologies and processes to improve efficiency and enhance the reporting platform
• Work at various and unanticipated worksites throughout the United States

Project Manager

• Lead projects involving the design, development, and delivery of data-driven solutions for insurance-industry clients
• Perform advanced data engineering, including building and maintaining ELT/ETL data pipelines
• Design data models using data warehousing concepts such as STAR and Medallion architecture
• Create interactive dashboards using Power BI or Tableau
• Deploy scalable, high-performance solutions on cloud platforms such as SAS, Snowflake, or AWS
• Engage stakeholders, gather requirements, and present findings
• Translate business needs into technical solutions
• Manage analyst/engineer teams and oversee workstreams for timely delivery

Application Engineer

• Lead the end-to-end lifecycle of data and application engineering projects, including requirements gathering, design, development, deployment, and production support
• Architect and implement cloud-based data pipelines using distributed and streaming technologies for healthcare analytics
• Oversee scalable applications and APIs for ingestion, processing, and delivery of healthcare data using microservices architecture
• Manage cross-functional teams across data, application, and integration domains
• Collaborate with product managers, architects, and client stakeholders to define technical requirements and prioritize solution enhancements
• Provide technical leadership on Google Cloud Platform, Apache Beam, Airflow, Kubernetes, FastAPI, Flask, Redis, and Shell scripting
• Ensure project alignment, technical compliance, and timely delivery
• Work at various and unanticipated worksites throughout the United States

Senior Manager – Data, Application Engineering

Business Intelligence Analyst

• Deliver advanced data analytics and Business Intelligence solutions supporting client-driven strategic decision-making
• Develop optimized SQL queries and perform in-depth data assessments for reporting and analytics readiness
• Design, develop, deploy, and validate scalable BI reporting and data visualization solutions using Tableau, Power BI, and/or ThoughtSpot
• Apply visualization standards, unit testing, and data validation to ensure accuracy, data integrity, and functionality
• Migrate manual reporting processes into standardized, automated environments through ETL workflows using Alteryx, Dataiku, Python, or equivalent tools
• Collaborate with product owners, operations leaders, client partners, and technical teams to gather reporting requirements and translate business needs into technical specifications
• Improve metrics and reporting structures through standardized dashboards, automated workflows, and mobile-enabled information delivery
• Manage project tasks, develop communication materials and executive-ready presentation decks, coordinate onshore and offshore deliverables, and ensure timely completion
• Develop and analyze test and control datasets; measure program performance, ROI, and statistically meaningful changes
• Present analytics findings, methodologies, and recommended business actions to senior leadership and external clients
• Identify and deploy AI-driven automation, AI agents, and automated decision workflows within the BI ecosystem
• Support cloud-based analytics implementations using GCP Cloud, BigQuery, and related cloud services
• Work at various and unanticipated worksites throughout the United States; telecommuting permitted

Business Intelligence Manager

Vice President

• Lead analytical initiatives for unsecured lending portfolios, including personal loans and credit cards
• Provide strategic advisory, policy development, and operational oversight in credit risk analytics
• Lead and manage teams and deliver insights through advanced analytics and BI tools
• Design and implement A/B testing frameworks using Design of Experiments (DOE)
• Perform portfolio analytics to monitor performance, identify emerging risks, and recommend mitigation strategies
• Apply machine learning and AI techniques, including Random Forest, Gradient Boosting, and NLP, to risk prediction models
• Build and maintain BI frameworks and dashboards using Power BI, Tableau, and Excel
• Conduct regression, clustering, time-series, and statistical modeling
• Partner with legal, compliance, and audit teams on regulatory standards and risk appetite
• Present analytical findings to senior stakeholders and executive leadership
• Collaborate with cross-functional teams to optimize processes and automate data workflows
• Evaluate remediation analytics and restitution plans for policy and regulatory compliance
• Manage data infrastructure using AWS, Snowflake, and Databricks
• Position may work at various and unanticipated worksites throughout the United States

Assistant Vice President

Full-stack Engineer

• Design, develop, and maintain custom AEM components, templates, and workflows across Sites, Assets, and Forms
• Use the AEM authoring interface to support QA, testing, and collaboration with content authors
• Integrate AEM with third-party services and internal systems, including personalization engines, analytics, and asset repositories
• Participate in technical design discussions and solution architecture with the Solutions Director and implementation partner
• Ensure platform stability, performance, and security through AEM development best practices
• Support international site rollouts, localization workflows, multilingual services, and multi-site management
• Troubleshoot and resolve bugs and platform issues with QA and operations teams
• Provide technical guidance to junior developers or partner teams
• Develop and enforce component libraries, code standards, and documentation
• Collaborate with DevOps on builds, deployments, and environment setup

AEM Full Stack Developer

• Design, develop, and maintain scalable enterprise applications and cloud-native solutions
• Lead technical design discussions, establish architectural standards, and guide engineering teams
• Develop and support Python applications and RESTful APIs using FastAPI, Flask, or similar frameworks
• Build and maintain microservices, distributed systems, and event-driven architectures for high-volume business processes
• Design, optimize, and support cloud-native solutions on Google Cloud Platform
• Implement Docker-containerized applications and orchestrate deployments through Kubernetes (GKE)
• Develop and maintain automated CI/CD pipelines
• Collaborate with product owners, architects, data engineers, and business stakeholders to define and deliver technical solutions
• Design and support Kafka or similar streaming and messaging solutions
• Develop scalable data processing solutions using BigQuery, BigTable, and SQL-based platforms
• Ensure application reliability, performance, security, observability, and operational excellence through monitoring and optimization
• Design, implement, and operationalize Generative AI solutions, including LLM-powered applications, RAG, and AI agent workflows
• Integrate enterprise applications with Vertex AI, Gemini, OpenAI, Claude, or similar platforms
• Perform code reviews, mentor engineers, and promote software engineering best practices
• Troubleshoot complex production issues, perform root cause analysis, and implement preventative solutions
• Drive continuous improvement in architecture, automation, development processes, and engineering standards
• Communicate technical concepts to technical and non-technical stakeholders and support strategic technology initiatives

• Define and drive enterprise data architecture strategies aligned with business objectives and technology roadmaps
• Design scalable, secure, and high-performance data platforms using Microsoft Fabric, Azure, and Databricks
• Establish architecture standards, reusable design patterns, and governance frameworks
• Lead cloud data modernization and migration initiatives from legacy platforms to cloud-native architectures
• Create architecture blueprints, reference architectures, and implementation roadmaps
• Architect and implement Microsoft Fabric Lakehouse, Fabric Data Warehouse, Data Pipelines, Real-Time Analytics, OneLake, and Power BI integrations
• Design Medallion Architecture within Microsoft Fabric
• Drive Fabric deployment strategies, performance optimization, and environment governance
• Implement security, access controls, lineage, monitoring, and data lifecycle management
• Design and implement Azure enterprise data solutions and ingestion, transformation, storage, and consumption frameworks
• Drive cloud adoption and optimization initiatives
• Architect and optimize Databricks Lakehouse solutions
• Lead Apache Spark, PySpark, Delta Lake, Unity Catalog, Databricks Workflows, Auto Loader, and Delta Live Tables implementations
• Design large-scale batch and real-time data pipelines
• Optimize Spark processing, cluster utilization, and workload performance
• Define data governance standards and implement metadata management, lineage, cataloging, and data quality frameworks
• Partner with security teams on data privacy, compliance, and regulatory adherence
• Enable business-friendly data discovery and self-service analytics
• Collaborate with business leaders, product owners, engineering teams, and program stakeholders
• Translate business requirements into scalable technical architectures
• Lead architecture reviews, design workshops, and solution governance forums
• Provide technical leadership and mentorship to data engineering teams

Data Architect – Microsoft Fabric, Azure Data Platform

• Build and scale Snowflake Centre of Excellence capabilities across architecture, engineering, governance, and FinOps
• Define reference architectures, reusable assets, frameworks, and accelerators
• Drive capability development, hiring strategy, and upskilling initiatives
• Establish standards for delivery quality, security, and performance
• Own end-to-end Snowflake architecture for enterprise-scale programs
• Translate business goals into data platform strategies
• Design data ingestion, transformation, orchestration, modelling, and consumption solutions
• Lead architecture governance and design reviews
• Lead large-scale Snowflake implementations and transformations
• Define and track delivery KPIs, FinOps cost optimisation, and performance metrics
• Ensure adoption of CI/CD, DataOps, and DevSecOps practices
• Act as escalation point for complex technical challenges
• Partner with clients on data strategies, roadmaps, and transformation journeys
• Lead solution workshops, proposals, and executive discussions
• Provide thought leadership in Snowflake, Data Engineering, and Analytics
• Drive account growth through cross-selling and innovation-led proposals
• Mentor architects and engineers across projects
• Build internal communities around Snowflake, dbt, the modern data stack, and cloud-native data engineering
• Promote best practices in coding, modelling, and governance

Senior Technical Lead, Snowflake

• Build and scale Snowflake CoE capabilities across architecture, engineering, governance, and FinOps
• Define reference architectures, reusable assets, frameworks, and accelerators
• Drive capability development, hiring strategy, and upskilling initiatives
• Establish standards for delivery quality, security, and performance
• Own end-to-end Snowflake architecture for enterprise-scale programs
• Translate business goals into data platform strategies
• Design data ingestion, transformation, orchestration, modelling, and consumption solutions
• Lead architecture governance and design reviews
• Lead large-scale Snowflake implementations and transformations
• Define and track delivery KPIs, cost optimisation, and performance metrics
• Ensure adoption of CI/CD, DataOps, and DevSecOps practices
• Act as escalation point for complex technical challenges
• Partner with clients on data strategies, roadmaps, and transformation journeys
• Lead solution workshops, proposals, and executive discussions
• Provide thought leadership in Snowflake, Data Engineering, and Analytics
• Drive account growth through cross-selling and innovation-led proposals
• Mentor architects and engineers across projects
• Build internal communities around Snowflake, dbt / modern data stack, and cloud-native data engineering
• Promote best practices in coding, modelling, and governance