Lead Data Scientist

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. 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.

Primary Responsibilities:

• Drive client value by:
  • Creating innovative solutions driven by exploratory data analysis from diverse datasets
  • Responsible for developing/delivering end-to-end Machine Learning projects/solutions that have a high degree of value, ambiguity, scale and complexity
  • Ability to coach/guide follow data scientists and accountable for delivering advanced analytics products
  • Using an analytical approach to design, develop, and implement data enrichments, predictive models, and advanced algorithms that lead to expanded value extraction from data
  • Leading efforts for applied use of machine learning to drive process optimization and transformation
  • Applying 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
  • Creating artifacts like STM, HLD, LLD for hardening prototypes into production (prototype to hardening)
  • 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
  • Designing and promoting best practices related to data enrichment, advanced modeling, and algorithm creation in support of analytically driven insight
  • Collaborating with business intelligence architects and domain analysts to maximize the effectiveness of business intelligence tools, dashboards, and other dynamic reporting capabilities
  • Leading efforts to build sophisticated data enrichment processes that server as the single source of truth to expanded insights on base data
  • Ensuring complex analytics adhere to statistical best practices
• 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 regard 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:

• Bachelors degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)
• 8+ years of combined experience in data science, data enrichment, and advanced modeling
• 8+ years of experience creating models/solutions using Python, Spark-SQL, Scala or other similar coding language
• 8+ years of experience manipulating large data sets through statistical software (ex. R, SAS) or other methods
• 5+ years of experience managing complex data projects and programs
• 5+ years of experience creating healthcare analytics
• Hands on experience in Microsoft Azure, Databricks, Mlflow and model deployment frameworks
• Hands-on experience in implementing and training machine learning algorithms and statistical analyses, including for example non-parametric tests,
• linear mixed models, modern supervised and unsupervised machine learning algorithms such as SVM, random forest, PCA, t-SNE, clustering, deep learning, and LLMs
• Highly proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages
• Proven excellent communication and presentation skills
• Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML)