Data Scientist / ML Engineer - Analytics and Insights Engineer III
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 Analytics and Insights Engineer III on the AI & Data team, you will be responsible for conducting research and development using programming, statistics, and machine learning in the federal healthcare space. You will translate Medicare policy and operational problems into statistical and machine learning approaches that support production model design and deployment. You will build, validate, tune, and operationalize predictive models with attention to assumptions, bias, leakage, generalization, and performance. You will develop production-quality Python code and machine learning pipelines that are tested, documented, version-controlled, and scalable for large data volumes. You will 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 in Statistics, Mathematics, Computer Science, Economics, Physics, Operations Research, or another quantitative field
- 2+ years of experience building and deploying data science or machine learning solutions
- 2+ 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
Benefits
- Discretionary annual incentive program
- Competitive benefits package for project delivery-focused professionals
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
