We are seeking an AI and Data Science Engineer III to help transform workforce and personnel data into actionable insights. In this role, you will apply data science, operations research, and visualization techniques to develop predictive models, decision-support tools, and interactive analytics solutions. The role supports workforce planning use cases such as attrition prediction, supply and demand forecasting, accession planning, and skill-gap analysis. You will also help deliver AI-enabled solutions that allow stakeholders to engage with data and model outputs in more accessible and dynamic ways.

Work you'll do

As an AI and Data Science Engineer III on the team, you will be responsible for:

• Building and maintaining predictive models for workforce analytics, including attrition modeling, supply and demand forecasting, accession planning, skill-gap analysis, and retention risk scoring using Python and/or R
• Applying operations research methods such as optimization, simulation, queuing theory, and scenario analysis to workforce planning challenges
• Designing and developing interactive dashboards and visualizations in Tableau and Python-based tools to communicate model outputs to technical and non-technical stakeholders
• Developing AI-enabled and large language model-powered tools that allow users to query workforce data and analytics outputs using natural language
• Documenting model methodology, assumptions, validation results, and limitations, and partnering with data engineering resources to support reliable data inputs and data quality standards

A successful candidate would possess these skills:

• 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

The team

The team focuses on process engineering and automation using a range of tools and technologies, including artificial intelligence, robotic process automation, agentic solutions, and scripting. The team develops scalable solutions that improve decision-making, increase efficiency, and expand access to data-driven insights. This role contributes to those efforts by helping turn workforce data into predictive, interactive, and operationally useful analytics products.

Qualifications

Required:

• 4 years of experience with Python
• 4 years of experience with advanced statistical analysis and modeling
• 4 years of experience with Tableau
• 4 years of experience with machine learning
• Bachelor's degree
• Active TS/SCI with polygraph clearance
• Ability to travel 10-25%, 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.

Preferred:

• Experience with Software Development Life Cycle (SDLC) processes

For individuals assigned and/or hired to work in Maryland, Deloitte is required by law to include a reasonable estimate of the compensation range for this role. This compensation range is specific to Maryland and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $119,000 to $198,400.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.