The resource is currently expected to come onsite once per month.
Meetings rotate between multiple locations:
MedStar/Met Square (DC)
Merriweather (Maryland)
Occasional Western office
Locations may alternate monthly to accommodate team members across Maryland and Virginia.
Important clarification:

Onsite frequency may increase to up to 2–3 times per month in the future.
Strong preference for local DMV candidates to support in-person collaboration.
Team & Project Context

The AI/ML team consists of approximately 10 members, with 2–3 engineers actively working in the ML space.
The team builds and maintains prediction models related to:
Providers
Members
Claims
Some models (provider and member models) are already live and operational.
Core Responsibilities

The selected resource will:

Work end-to-end across the full AI/ML lifecycle, including:
Data ingestion
Data preprocessing
Feature engineering
Model training
Model validation
Model deployment
Maintain existing ML models currently in production.
Enhance and improve current models.
Develop new models, including Generative AI solutions, using established AI/ML pipelines.
Collaborate closely with the broader AI team through regular syncs and working sessions.
Mandatory Technical Requirements

Must-Have Skills:

AWS SageMaker – mandatory and critical
Python – primary programming language
SQL & NoSQL databases – mandatory
At least 1 year of hands-on Generative AI experience

Preferred / Nice-to-Have Skills:

Cloud-based data platforms:
Snowflake (preferred)
Databricks or other cloud data sources acceptable
Big data tools:
Spark (optional)
Hive (optional)
AWS GenAI tools:
Bedrock (optional)
Agent Core (optional)
Healthcare / payer insurance domain experience – nice to have, not required

Responsibility:

* Develop algorithms, write scripts, build predictive analytics, use automation, apply machine learning, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help senior leadership make informed decisions.
* Provide the team with a deep understanding of their data, what it all means, and how they can use it.
* Help with discovering the information hidden in vast amounts of data, and help with making smarter decisions to deliver even better products.
* Applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with products.
* Development new ML model(s) as well as maintaining existing ones and their processes.
* Development Gen AI solution using AI platform like AWS Segamaker, AWS Bedrock, AWS AgentCore.
* Select features, building and optimizing classifiers using machine learning techniques, data mining using state-of-the-art methods, and, enhancing data collection procedures to include information that is relevant for building analytic systems.
* Responsibilities will also include processing, cleansing, and verifying the integrity of data used for analysis and doing ad-hoc analysis and presenting results in a clear manner.
* Creating automated anomaly detection systems and constant tracking of its performance.

Requirements:

* Master's Degree or Ph.D. in STEM with 2+ years preferred OR Bachelor's Degree in STEM with 7+ years.
* Experience in predictive modeling, data science, machine learning, or user and entity behavior analytic development.
* Experience in developing predictive, prescriptive, optimization, and forecasting models, including the use of contemporary techniques such as and not limited to support vector machines, neural networks, and gradient boosting.
* Experience in developing of Generative AI solution with LLM and custom model to provide AI solution to business.
* Experience in interpreting results from statistical and mathematical models.
* A minimum of two years' experience in applying Data Science/ Analytics to Health Insurance/Health Care related problems/use cases.
* At least 1 years focused on applications of Generative AI solution.
* Experience in programming languages like Java, Python and/or R for complex data manipulation, statistical analysis, and machine learning.
* Experience in Analytic development with streaming and a Hadoop ecosystem (Hive, Spark, etc.)
* Experience in SQL, NoSQL, graph-based, Key/Value stores, document stores.
* Experience with cloud base data platform like Snowflake and use trainin/build model.
* Experience with one or more cloud services (AWS Sagemaker, MS Azure)
* Experience applying machine learning to real-world production systems, analytic development based on SparkML and other ML libraries.
* Experience in advanced data visualizations and interpretation using data visualization tools is plus (e.g., Tableau, Power BI).
* Familiarity with common Linux/Unix command line tasks and version control software like git or svn preferable.
* Using and developing statistical analysis, modeling, simulation, and machine learning methods.
* Comfort with complex mathematical concepts and models.
* Experience with Agile Methodology/Scrum Development and DevOps
* History of solving difficult problems using a scientific approach highly preferred
* Ability to communicate and present the work effectively and influence others
* Ability to work in a fast paced environment and shift gears quickly