AI and Data Science Engineer II

About the role

As an AI and Data Science Engineer II on the Advertising, Marketing & Commerce team, you will be responsible for:

• Translating business goals into machine learning use cases and model design approaches.
• Performing exploratory data analysis to identify relationships, opportunities to influence outcomes, and cross-channel attribution patterns.
• Applying clustering, sampling, feature transformation, and predictive modeling techniques to develop and refine solutions.
• Building proofs of concept, interpreting model results, and validating that solutions perform as intended.
• Collaborating with clients and cross-functional teams, including analytics and data engineering teams, throughout solution development and delivery.

Responsibilities

• 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

Deloitte's Advertising, Marketing & Commerce team creates content and experiences that inspire action. We design and implement technology platforms for personalized marketing across all digital touchpoints, specializing in customer-centric B2B and B2C solutions. Our in-house agency engages customers throughout their journey, working on projects like AdTech, MarTech, campaign automation, CRM, and lead-to-loyalty orchestration. Join us to drive impactful customer interactions and business growth.

Qualifications

• Bachelor's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
• 2+ years of industry experience outside of academia applying data science or machine learning methods
• Experience translating business goals into machine learning use cases and model design
• Experience performing exploratory data analysis and developing predictive models
• Ability to travel 30%, 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:

• Master's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
• Experience manipulating large marketing data sets and performing extract, transform, and load activities
• Experience with boosted trees, logistic regression, classification techniques, unsupervised models, large language models, or experimental design
• Experience with data sets generated in advertising technology or marketing technology environments
• Experience presenting complex data insights to non-technical audiences
• Experience with deep learning architectures or reinforcement learning

Pay

A reasonable estimate of the current range is $86,700 – $170,900. 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.