Senior Data Scientist - Remote

UnitedHealth Group•Eden Prairie, MN

1d•$91,700 - $163,700•Remote

About The Position

Optum's Payment Integrity Decision Intelligence is expanding and seeking a Senior Data Scientist to help drive our mission of achieving accurate and effortless claims payments through advanced analytics and machine learning. We are looking for a motivated professional with expertise in machine learning, large language models (LLMs), and healthcare analytics who is passionate about solving complex business problems with data. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

3+ years of experience developing and deploying predictive models using machine learning, deep learning, NLP, or related techniques
3+ years of experience using machine learning libraries and frameworks such as Scikit-learn, PyTorch, TensorFlow, or SparkM
3+ years of professional experience programming in Python for data science and machine learning applications
2+ years of experience writing complex SQL queries for data extraction, transformation, and analysis
1+ years of hands-on experience with large language model (LLM) frameworks such as Hugging Face Transformers, LangChain, or OpenAI APIs
1+ years of experience working with cloud platforms such as AWS, Azure, or GCP
Experience using Apache Spark for distributed data processing and large-scale data transformations
Experience using Git for version control and collaborative software development
Demonstrated problem-solving, communication, and collaboration skills

Nice To Haves

Experience working with healthcare data, claims analytics, or payment integrity solutions

Responsibilities

Utilize large language models (LLMs) to enhance analytic methodologies and support innovation across core product lines
Design, develop, and maintain data science solutions, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring
Collaborate with engineering and product teams to implement and maintain scalable machine learning models in production environments
Communicate technical findings, insights, and recommendations clearly to both technical and business stakeholders
Support innovation initiatives in machine learning and AI by evaluating and applying new techniques and technologies
Independently analyze complex data problems and recommend actionable solutions that deliver measurable business value
Contribute to best practices in model development, code quality, documentation, and reproducibility
Partner with cross-functional teams to ensure analytical solutions align with business objectives and operational needs
Assist in evaluating and implementing emerging technologies such as foundation models, retrieval-augmented generation (RAG), and advanced NLP techniques