Senior Data Scientist - Risk Adjustments Analytics - Associate Vice President, Data Management

Deloitte•Washington, DC

29d•$167,000 - $278,300•Onsite

About The Position

Our Deloitte AI & Engineering team transforms technology platforms, drives innovation, and helps make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. As an Associate Vice President, Data Management on the AI & Data team, you will be responsible for: Conduct research and development using programming, statistics, and machine learning in the federal healthcare space Translate Medicare policy and operational problems into statistical and machine learning approaches that support production model design and deployment Build, validate, tune, and operationalize predictive models with attention to assumptions, bias, leakage, generalization, and performance Develop production-quality Python code and machine learning pipelines that are tested, documented, version-controlled, and scalable for large data volumes Collaborate with engineers, analysts, subject-matter experts, and government stakeholders to communicate model performance, limitations, and methodology, and to support auditability and knowledge transfer

Requirements

Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others
Bachelor’s degree
10+ years of experience building and deploying data science or machine learning solutions
10+ years of experience conducting research using statistical methods, data science, and machine learning
Ability to travel 15-20%, on average, based on the work you do and the clients and industries/sectors you serve
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Nice To Haves

Master’s degree or Doctor of Philosophy degree in Statistics, Mathematics, Computer Science, Economics, Physics, Operations Research, or another quantitative field
Experience with Python and data science or machine learning libraries such as NumPy, pandas, scikit-learn, SciPy, or statsmodels
Experience with object-oriented programming, version control using Git, testing, and code review
Experience supporting healthcare or Medicare programs
Experience working with claims, enrollment, or administrative healthcare data, including Centers for Medicare & Medicaid Services data, International Classification of Diseases codes, Current Procedural Terminology codes, or Healthcare Common Procedure Coding System codes
Experience applying probability, statistics, linear algebra, or optimization to machine learning model development

Responsibilities

Conduct research and development using programming, statistics, and machine learning in the federal healthcare space
Translate Medicare policy and operational problems into statistical and machine learning approaches that support production model design and deployment
Build, validate, tune, and operationalize predictive models with attention to assumptions, bias, leakage, generalization, and performance
Develop production-quality Python code and machine learning pipelines that are tested, documented, version-controlled, and scalable for large data volumes
Collaborate with engineers, analysts, subject-matter experts, and government stakeholders to communicate model performance, limitations, and methodology, and to support auditability and knowledge transfer