Data Scientist @ Optum

Primary Responsibilities:

• Build and productionize ML/GenAI solutions using Python and Spark
• Integrate LLM capabilities (APIs/agents) into applications and workflows
• Design and maintain data pipelines for model training and inference
• Conduct experiments, track metrics, and iterate based on results
• Collaborate with product, data engineering, and platform teams to deliver features end-to-end
• Document solutions and follow best practices for version control, testing, and CI/CD
• Conduct experimentation, model evaluation, A/B testing, and performance tuning using tools like Mlflow
• Develop & maintain scalable data pipelines for model training, validation inference using Spark/Databricks
• Implement RAG pipelines, embedding-based search, and LLM-driven text generation
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor's/ Master's degree (preferably in information technology, data science, engineering, math, computer science, analytics, engineering or other related field)
• 3+ years of experience in handling/active development in data science projects
• 2+ years of experience in Microsoft Azure Cloud, Databricks, Mlflow, Spark SQL & Python
• Experience building ML models and/or integrating LLMs into real applications
• Experience using LLMs & Machine Learning Algorithms: Chat GPT, Claude, Llama Models, Linear & Logistic Regression, Time Series analysis, Support Vector Machine, K-Means clustering, K-Nearest Neighbors Decision Trees, Random Forest, Naive Bayes, PCA, SVD, Artificial Neural Networks, Association Rules, Genetic Algorithm, Optimization, Bagging and Boosting algorithms etc
• Expertise in developing, deploying, and optimizing end-to-end ML and GenAI solutions
• Proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages

Preferred Qualifications:

• Experience deploying and maintaining ML models in production
• Experience with model observability tools for insights into the behavior, performance, and health of your deployed ML models (tracking, alerting, compliance monitoring, etc.)
• Experience supporting analytical capabilities inclusive of reporting, dashboards, extracts, BI tools, analytical web applications and other similar products
• Familiarity with model versioning tools (MLFlow, etc.)
• Proven desire to continuously learn and seek new options and approaches to business challenges
• Proven willingness to leverage best practices, share knowledge, and improve the collective work of the team
• Proven ability to effectively communicate concepts verbally and in writing