Job description

Company Overview Index Analytics, LLC, is a rapidly growing, Baltimore-based small business providing health-related consulting services to the federal government. At the center of our company culture is a commitment to instilling a dynamic and employee-friendly place to work. We place a priority on promoting a supportive and collegial team environment and enhancing staff experience through career development and educational opportunities. Position Overview We are seeking a Junior BI Developer with foundational SQL, reporting, and data analysis skills, strong attention to detail, and a desire to build expertise in business intelligence development. This role is ideal for an early-career professional interested in developing hands-on experience with SAP BusinessObjects, enterprise reporting solutions, and business intelligence technologies in a federal client environment. Working under the guidance of senior developers, analysts, data teams, and business stakeholders, the Junior BI Developer will support the development, maintenance, testing, and troubleshooting of enterprise reporting solutions using SAP BusinessObjects, SQL, and related analytics tools. Responsibilities include assisting with report and universe development, creating and validating SQL queries, testing and validating report outputs, documenting report logic and technical specifications, and supporting ongoing reporting operations and production issue resolution. This position provides exposure to the full reporting solution lifecycle, including requirements analysis, design support, development, testing, deployment, maintenance, and continuous improvement of analytical products and reporting applications within enterprise business intelligence environments. Key Responsibilities • Design, develop, and maintain machine learning and deep learning models, including both traditional (e.g., regression, tree-based models) and neural network-based approaches. • 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. • Design and implement a scalable knowledge graph and semantic data model that captures relationships among policies, analytic use cases, data domains, information assets, products, and institutional knowledge, enabling advanced search, discovery, impact analysis, and AI-assisted knowledge retrieval. • 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. • Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets. • 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. • U.S. citizen or otherwise authorized to work in the United States and able to demonstrate physical residency in the U.S. for at least three (3) of the past five (5) years. Must be able to obtain a U.S. Federal government client badge and pass a Public Trust clearance. • Master’s degree in Computer Science, Data Science, or a related field required; PhD preferred. A minimum of six (6) years of experience or an equivalent combination of education and experience, with three (3) or more years of experience as a Data Scientist or in a similar role. • Strong experience in machine learning and statistical modeling, including supervised and unsupervised learning techniques, deep learning, and a solid foundation in probability, hypothesis testing, and regression. • Proven expertise in NLP and text analytics, including transformer-based architecture (e.g., BERT and related models), embeddings, vector databases, and semantic search systems. • Hands-on experience building LLM-powered applications, including prompt engineering, RAG architecture, and ideally agentic workflows or LLM orchestration frameworks, preferably within AWS environments (e.g., Bedrock). • Experience with developing and using knowledge graphs strongly preferred. • Advanced programming skills in Python (preferred) and/or R, with practical experience using ML and data libraries such as pandas, NumPy, scikit-learn, PyTorch, and TensorFlow. • Strong experience with AWS cloud and MLOps tooling, including SageMaker, S3, Glue, Airflow, and data stores such as Redshift and DynamoDB, along with version control (GitHub) and CI/CD pipelines (e.g., Jenkins). • Experience with backend systems and data integration, including data modeling and supporting APIs for web-based and production applications. • Experience working with large healthcare datasets, especially Medicaid, a plus • Strong written and verbal communication skills, with the ability to explain complex models and insights clearly. • Experience supporting CMS or other federal healthcare agencies is a plus. Disclaimer Index Analytics provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Requirements

Must-haves

Company Overview
Position Overview
Design, develop, and maintain machine learning and deep learning models, including both traditional (e.g., regression, tree-based models) and neural network-based approaches.
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.
Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets.
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.
Strong experience in machine learning and statistical modeling, including supervised and unsupervised learning techniques, deep learning, and a solid foundation in probability, hypothesis testing, and regression.
Proven expertise in NLP and text analytics, including transformer-based architecture (e.g., BERT and related models), embeddings, vector databases, and semantic search systems.
Hands-on experience building LLM-powered applications, including prompt engineering, RAG architecture, and ideally agentic workflows or LLM orchestration frameworks, preferably within AWS environments (e.g., Bedrock).
Strong experience with AWS cloud and MLOps tooling, including SageMaker, S3, Glue, Airflow, and data stores such as Redshift and DynamoDB, along with version control (GitHub) and CI/CD pipelines (e.g., Jenkins).
Experience with backend systems and data integration, including data modeling and supporting APIs for web-based and production applications.
Strong written and verbal communication skills, with the ability to explain complex models and insights clearly.

Nice-to-haves

Experience with developing and using knowledge graphs strongly preferred.
Advanced programming skills in Python (preferred) and/or R, with practical experience using ML and data libraries such as pandas, NumPy, scikit-learn, PyTorch, and TensorFlow.
Experience working with large healthcare datasets, especially Medicaid, a plus
Experience supporting CMS or other federal healthcare agencies is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlmachine learningmlawsllmaiagilepythonci/cd

Platform: paycom
Effort: medium