Immediate need for a Data Scientist to support our customer, a Federal Healthcare Insurance organization. The selected candidate will be responsible for identifying and solving business problems by using various numerical techniques, algorithms, and models in statistical modeling, machine learning, GenAI, operations research, and data mining. The selected candidate will use advanced analytical capabilities to support data science initiatives. Communicates across product teams and with customers and educates on artificial intelligence, machine learning, and statistical models. Acting as a liaison and interface between analytics, business units and other departments.

Each of our clients data scientists owns their own high-impact projects, whether it is a new modeling technique delivering better predictions, a new analysis and visualization highlighting weak spots in our pipelines, or a new tool that can help the team-s workflow. We are looking for a Data Scientist who can leverage their prior experience and take on and lead large data science projects, from inception to completion. In addition to contributing technically throughout the project, you will also responsible for: working with product to refine product requirements, managing/coordinating the efforts of other data scientists contributing to the project, and interfacing with stakeholders throughout the company.

This position is a remote opportunity with one meeting per quarter in Reston VA. Want to learn more about this long term contract opportunity? Then you should contact Elite Technical right away for consideration!

Required Skills

Requirements:
- 6+ years as a Data Scientist, with 2-3 years of experience in both GenAI and Machine Learning (ML). Must have strong NLP (natural language processing) experience.
-Strong Data Modeling expertise: Proficiency in data science modeling - Machine Learning, Deep Learning, Decision Trees, Random Forest, Neural Networks, Supervised/Unsupervised Learning, Forecasting, Predictive Modeling and Clustering.
- Strong background in machine learning using unsupervised and supervised methods.
- Deep knowledge of fundamentals of machine learning, data mining and statistical predictive modeling, and extensive experience applying these methods to real world problems
- Strong Relational DB Structure understanding
-Experience with indexing data (taking raw unstructured data and moving it to structure)
- Understanding of Large Language Models (GPT or similar)
- Python and SQL are required. Advanced proficiency in Python and Spark/Scala for classical statistical analysis and data modeling, machine learning and ETL processes. Intermediate to advanced ability to create data visualizations using Python.
- Experience with machine learning methods like k-nearest neighbors, random forests, ensemble methods and more
-Understanding of Data Engineering or Data Analyst (career progression from either to Data Scientist is preferred)

Preferred:
- AWS Cloud knowledge: (AWS migration considered big plus). Knowledge in one or more AWS Service SageMaker, open to AWS Glue, Athena, Lambda etc..
-Healthcare Insurance Industry experience
- agenticAI
- Fine tuning of LLM
- RAG (retrieval augmented generation)