• Develop technical solutions that meet business requirements, aiming to create scalable and high-performance applications; • Develop batch systems and REST APIs in Python based on provided documentation, creating applications that meet user requirements; • Maintain web portals; • Identify and fix incidents and maintain systems according to problem descriptions and log analysis; • Prepare technical documentation for implemented solutions; • Write unit tests; • Interact with the business area to clarify business requirements, validate developed systems, and provide technical input in alignment meetings; • Experience with Agile methodologies is desirable; • Develop and evaluate generative AI (LLMs) solutions applied to real business problems such as product recommendation, document analysis, chatbots, and collections strategies; • Conduct experiments to optimize models, including prompt engineering, fine-tuning, and RAG (Retrieval-Augmented Generation) techniques; • Define and implement evaluation metrics for generative models (e.g., quality, factuality, consistency, and bias); • Perform robust statistical analyses to validate results, including hypothesis testing, confidence intervals, and simulations; • Identify risks and propose solutions to mitigate hallucinations, biases, and reliability issues.

• Identify long-term research goals as well as intermediate milestones for AI models and applications. • Execute research that pushes forward the state of the art in AI domains such as predictive health outcomes, LLMs, and Generative AI. • Directly contribute to experiments training AI models, including experimental design, writing reusable code, running evaluations, and preparing results for broader circulation. • Publish research in top tier conferences and journals in the diabetes, health sensing, and technology communities. • Contribute to the evaluation and improvement of the safety of our models and systems, identifying areas of risk and proposing mitigation strategies.

Role Description We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production-ready solutions by translating complex business problems into data-driven approaches and model-based outputs. Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real-world use cases. The role includes hands-on model development, feature engineering, and integration into production systems within cloud environments. The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred. Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting. This position is open to remote or hybrid. Qualifications - Strong problem-solving skills with an emphasis on product development. - Strong foundation in machine learning, statistical modeling, and data science techniques. - Experience building and deploying machine learning models in production environments. - Familiarity with modern AI approaches, including: - Natural language processing (NLP) - Large language models (LLMs) - Retrieval-Augmented Generation (RAG) - Feature engineering and model evaluation techniques. - Experience working with cloud platforms such as Azure, AWS, or similar ecosystems. - Familiarity with data pipelines, APIs, and integration patterns. - Proficiency in programming languages such as Python and database management including SQL. - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications. - Excellent presentation and written/verbal communication skills. Requirements - Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master’s preferred. - 2–5+ years of experience in data science, machine learning, or related roles. - Experience developing and deploying machine learning models in production environments. - Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar. - Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred. - Experience working within enterprise software environments and SDLC practices preferred. Benefits - Comprehensive benefits package for full-time regular employees, including: - Medical (HDHP) w/Pharmacy - Dental - Vision - Long Term Disability - Health Savings Account - Flexible Spending Account Options - Life Insurance - Accident Insurance - Critical Illness Insurance - Pre-paid Legal Insurance - Parking and Transit FSA accounts - 401K and ROTH 401K - Paid time off Company Description CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers’ compensation, auto, health and disability management industries. CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients. We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities. Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

• Perform analyses on large sets of data to extract practical insights • Define data requirements and support the implementation of data specs • Maintain the Spotify Ads Manager’s data and reporting ecosystem • Design and conduct experiments for user and advertiser metrics • Communicate data-driven insights and recommendations