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Job Details


Data Science Manager (24477)

Branch Manager




Arlington, Virginia, United States

Are you looking to make an impact by helping agencies meet their mission goals through successful implementation and operation of their regulatory, mission or compliance programs? Are you ready to help our clients mitigate risks that arise from transformational core business operational change or ongoing operations? Are you interested in helping clients transform how they operate their business to be more effective? If so, Deloitte's Regulatory Compliance team could be the place for you! Our team brings professionals with diverse skillsets including deep experience in industry, AI-enabled data analytics, statistical modeling, and cloud technologies to help our clients preserve their reputation and public trust of their agencies while managing regulatory demands.

Work you'll do

  • Drive day-to-day development, maintenance, and operations of a suite of advanced machine learning models and AI pipelines on a growing AI platform
  • Lead a team of data scientists, engineers, and model validation professionals in designing and releasing new capabilities to advance data science techniques and improve the trust and transparency in the AI modeling lifecycle
  • Interpret and translate model results, metadata, trends, and takeaways to team members, clients, and executive leadership with varying levels of subject matter knowledge
  • Oversee the execution and effectiveness of key modeling governance activities around change management, performance monitoring, and testing, in alignment with industry best practices
  • Collaborate with platform engineers, data engineers, system designers, architects, database administrators, and cyber security risk professionals to assist in the overall design of production modeling systems and processes to enhance the value of modeling insights delivered to our clients
  • Responsible for mentoring and developing modeling staff and managers

The team

Deloitte's Government and Public Services (GPS) practice - our people, ideas, technology and outcomes-is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of over 15,000+ professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

We bring a diverse set of forward thinking capabilities to help agencies proactively manage risks they face in their dynamically changing environments. Our team assesses and transforms the process, controls, and/or infrastructure needed to help our clients address a wide variety of regulatory and compliance risks. We leverage solutions that align to the end-to-end regulatory lifecycle through leveraging AI technology and innovative solutions that incorporate industry as well as domain knowledge.



  • Bachelor's Degree in a quantitative field, such as computer science, mathematics, statistics, economics, or physics
  • Must be lega lly authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
  • Must be able to obtain and maintain the required Public Trust clearance for this role
  • 6+ years of experience performing, validating, managing, or leading teams in big data analytics, modeling, and machine learning
  • Hands-on development experience of AI and machine learning models, packages, or cloud AI software
  • Experience across the entire model development lifecycle, including interacting with model risk management teams and executing model governance best practices to support trust in AI
  • Deep technical understanding, including proficiency in an analytical programming language, such as SAS, Python, or R, to provide clear technical direction and grow the skills of your team


• Master's degree or Ph.D. in a quantitative field, such as computer science, mathematics, statistics, economics, or physics

• Agile certification and experience with Agile ceremonies

• Cloud certifications (AWS, Azure, Google Cloud)

• Experience orchestrating MLOps pipelines (MLflow, Kubeflow)

• Development experience of explainable AI algorithms and frameworks (LIME, SHAP)

• Experience with designing controls for adversarial machine learning threats

• Published research in the field of AI ethics or AI trust

• Development of AI audit or governance frameworks

• CFA, FRM, INFORMS CAP, or similar industry certificate