Senior data Scientist

Requisition Number: 2389432
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
Positions in this function produce innovative solutions driven by exploratory data analysis from unstructured, diverse datasets typically measured in gigabytes or larger. Applies knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. Uses a flexible, analytical approach to design, develop, and evaluate predictive and prescriptive models and advanced algorithms that lead to optimal value extraction from the data. Works with analytics and statistical software such as SQL, R, Python, Hadoop and others to perform analysis and interpret data. This function is not intended for employees performing the following work: less complex analysis on small data sets; rules-based algorithmic or descriptive analytics; development of big data infrastructure. Generally work is self-directed and not prescribed.
Join the Enterprise Technology Infrastructure Platform Services ( ETIPS ) team, driving innovation and reliability across core systems.
Primary Responsibilities:

• Drive client value by:
  • Developing predictive models using various machine learning algorithms/best practices
  • Developing and running scripts for ML model inference
  • Testing various hypothesis and presenting back to the technical/non-technical audience
  • Performing cost benefit analysis for various DS initiatives
  • Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions
  • Creating artifacts like STM, HLD, LLD for hardening prototypes into production (prototype to hardening)
  • Be able to apply knowledge of data modeling, statistics, machine learning, programming, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to more actionable insights
  • Working with analytics and statistical software and products, such as SQL, R, Python, Hadoop and others to perform analysis and interpret data
  • Communicate the performance of the machine learning algorithms across an interdisciplinary team
• Create impact at scale by:
  • Developing and managing a comprehensive catalog of scalable data services that expand the value of analytical offerings
  • Looking for opportunities for continuous improvement/optimization of models in production
  • Data Drift
  • Champion (Prod Model) Vs Challenger (Enhanced Dev Model)
  • Implementing best practices on ML architecture/workflows etc
  • Collaborating with business intelligence architects and domain analysts to maximize the effectiveness of business intelligence tools, dashboards, and other dynamic reporting capabilities
• Works with less structured, more complex issues
• Serves as a resource to others
• Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications:

• Bachelor's Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)
• 5+ years of experience in handling/active development in data science projects
• 5+ years of experience in Microsoft Azure Cloud, Databricks, Mlflow, Spark SQL & Python
• Experience using Machine Learning Algorithms: 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.
• Understanding for data, schema, data model, machine learning and how to bring efficiency in big data related life cycle
• Proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages
• Proven skills to create opportunities using machine learning or artificial intelligence
• Proven excellent communication and presentation skills
• Proven solid analytical, problem-solving skills
• Proven cooperative and team player attitude
• Ability to design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
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