Index Analytics LLC

Full-stack Engineer

• Build, test, maintain, and enhance full stack applications and data solutions across the front end, back end, and database layers.
• Contribute across the software development lifecycle, including requirements analysis, technical design, implementation, testing, deployment, and production support.
• Develop and consume RESTful APIs to support integration between applications, data platforms, and enterprise systems.
• Build and maintain ETL/ELT data pipelines to support batch and near-real-time data processing, and implement data transformation workflows that are performant and maintainable.
• Develop and support data models, transformations, and workflows in Snowflake to enable scalable and efficient data processing.
• Use Apache Airflow to orchestrate, schedule, monitor, and troubleshoot data pipelines and automated workflows.
• Collaborate with infrastructure and application teams to deploy, support, and improve solutions in AWS.
• Implement application and data pipeline features that integrate with relational databases and AWS services such as S3 and related cloud resources.
• Partners with Cloud Engineering, DevSecOps, and application teams to implement infrastructure as code (IaC) and CI/CD pipelines for Snowflake objects and deployments.
• Monitor and troubleshoot application, pipeline, and integration issues in development and production environments, and document root cause and resolution steps.
• Work with cross-functional teams in an Agile environment to deliver application and data solutions that support business and user needs.

Senior Full Stack Engineer

Data Analyst

• Collect, validate, and analyze data from multiple sources
• Develop reports that communicate trends, risks, and performance insights
• Define, track, and maintain KPIs, baselines, and performance metrics
• Analyze and document current-state business processes
• Evaluate how data collection practices impact process performance
• Identify gaps in data capture, documentation, and workflows
• Translate analytical findings into actionable recommendations
• Establish and support feedback loops linked to operational changes
• Collaborate with stakeholders to gather requirements and ensure alignment

Junior Data Analyst

Data Scientist

• Serve as a technical lead on AI and machine learning initiatives, providing guidance on solution architecture, model selection, implementation approaches, and technical best practices.
• Mentor and support junior and mid-level data scientists through code reviews, knowledge sharing, technical coaching, and collaborative problem solving.
• Establish and promote best practices for MLOps, model evaluation, model monitoring, reproducibility, and responsible AI development
• Build and deploy end-to-end ML pipelines on AWS (e.g., SageMaker, S3, Glue) for scalable training, evaluation, and inference.
• Develop and implement advanced NLP solutions, including text classification, entity recognition, topic modeling, and semantic search using models such as BERT and transformer-based architectures.
• Design, build, and productionize RAG (Retrieval-Augmented Generation) systems, including document ingestion, embedding pipelines, vector search, and LLM orchestration.
• Develop LLM-powered applications, including prompt engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost.
• Contribute to agentic AI system design, including multi-step reasoning workflows, tool use, and orchestration of LLM-driven agents for complex tasks.
• Implement predictive analytics and statistical modeling to uncover patterns, trends, and insights from healthcare data.
• Evaluate emerging AI technologies, frameworks, and techniques and recommend their appropriate application to government healthcare use cases.
• Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets.
• Contribute to technical leadership across multiple AI initiatives while remaining an active hands-on developer and model builder.
• Build data visualizations, dashboards, and analytical tools to communicate findings clearly to technical and non-technical stakeholders.
• Evaluate model performance using appropriate metrics (e.g., accuracy, AUC, precision/recall) and present results in a clear, actionable manner.
• Collaborate in an Agile environment with cross-functional teams including engineers, analysts, and stakeholders.
• Recommend data-driven solutions and AI strategies aligned with CMS business needs and healthcare policy objectives.

Senior Data Scientist

Engineer

• Administer and maintain Salesforce environments, ensuring optimal performance, security, and user accessibility.
• Extensively work with Copado to set up, configure, and manage deployment pipelines for Salesforce.
• Collaborate with the development team to ensure smooth deployments and releases.
• Troubleshoot and resolve issues related to deployments, mergers, and environment synchronization.
• Lead and guide best practices around Salesforce DevOps, ensuring adherence to industry standards.
• Work closely with stakeholders to gather technical requirements, implement solutions, and provide post-deployment support.
• Regularly review and clean metadata in Salesforce environments.
• Keep abreast of the latest Salesforce updates and features, ensuring our environment leverages the best and latest functionalities.
• Assist in training and guiding other team members on best practices related to Salesforce and Copado.

Copado Engineer

Salesforce Developer

• Contribute to all technical aspects of the project, including designing, developing, testing, and deploying Salesforce applications throughout the full development lifecycle.
• Quickly learn and apply new Salesforce features, tools, and technologies, while effectively communicating with business owners, technical teams, development partners, and user groups to support solution delivery.
• Ensure development projects meet business and end - user requirements by identifying, troubleshooting, and resolving system issues to deliver reliable, high - quality solutions.
• Support proof - of - concept efforts and technical solutioning, helping establish the technical vision and partnering with developers to bring that vision to life.
• Collaborate closely with stakeholders and team members to enable timely project delivery, supported by strong verbal and written communication skills and effective documentation.

Investigator

• Examine and assess healthcare providers’ compliance related to healthcare legislation
• Conduct research and analysis, pulls information, cites regulations using regulatory language
• Draft and review detailed, substantive investigative reports, complaint summaries, and findings analyses
• Collaborate with other departments or agencies involved in healthcare regulation
• Mentor and guide junior investigators, supporting evidence collection, stakeholder interviews, and data analysis
• Prepare reports and provide recommendations based on investigative findings

Data Engineer

• Collaborate closely with stakeholders, cross‑functional and internal technical teams to gather requirements, document business rules and develop thorough understanding of the business context and objectives
• Collaborate to design secure, scalable, and cost‑optimized data solutions
• Design, build, and maintain scalable, reliable ETL/ELT data pipelines using AWS, Snowflake and Snowflake tools
• Develop and optimize data models, both conceptual and physical, to support analytics, reporting, dashboards and operational consumption
• Implement data quality, validation, and monitoring frameworks to ensure accuracy and reliability
• Ensure data workflows are modular, testable, and properly version‑controlled
• Operationalize pipelines with monitoring, alerting, and automated recovery mechanisms
• Conduct advanced data analysis using languages such as Python and SQL
• Develop documentation to include data models, data dictionaries, and data usage guides
• Improve end-to-end performance of data workflows
• Build and maintain CI/CD pipelines using Jenkins to support automated testing, deployments, and continuous integration
• Meet schedule deadlines and commitments with a high-level of quality of deliverables
• Collaborate with a team of cross-functional resources in an Agile delivery environment to deliver iterative value

Senior Data Engineer

• Support the design, development, testing, and maintenance of full stack web applications across the front end, back end, and database layers.
• Participate in the full software development lifecycle (requirements, design, implementation, testing, deployment, and production support) with mentorship from senior engineers.
• Develop and consume RESTful APIs to enable integration between applications and enterprise systems under guidance.
• Collaborate with infrastructure and application teams to deploy and support applications in AWS.
• Implement application features that read/write data to relational databases (e.g., PostgreSQL/Aurora) and integrate with AWS services (e.g., S3, Secrets Manager, SSM) following team patterns.
• Monitor and troubleshoot application and integration issues in development and production environments; document root cause and remediation steps.
• Contribute to Infrastructure as Code (IaC) templates for infrastructure, application, and database changes that are promoted through CI/CD pipelines.
• Support CI/CD pipelines (e.g., Jenkins) by updating build steps, reviewing logs, and helping resolve failed deployments.
• Follow CMS security, privacy, and DevSecOps requirements by implementing secure coding practices and completing required documentation and reviews
• Triage operational issues using standard monitoring and analysis tools (e.g., AWS CloudWatch, Splunk) and escalate appropriately.
• Assist in remediating security vulnerabilities by applying patches/updates to application dependencies and supporting infrastructure under guidance.

Junior Full Stack Engineer

• Design, develop, and maintain web applications across front-end and back-end
• Collaborate with teams to understand business requirements
• Ensure high performance and responsiveness of applications
• Manage databases and implement security best practices
• Write clean, scalable code
• Solve complex engineering problems
• Participate in Agile team environment
• Collaborate and review code with peers
• Understand requirements and translate them into specs

Full Stack Engineer

• Design, develop, and maintain machine learning models
• Build and deploy ML pipelines on AWS
• Develop advanced NLP solutions
• Design and productionize RAG systems
• Develop LLM-powered applications
• Implement predictive analytics and statistical modeling
• Perform data mining and exploratory data analysis
• Build data visualizations and dashboards
• Evaluate model performance and present results
• Collaborate in an Agile environment