Lead AI and Data Science Engineer II

Deloitte • Boston, MA

1d • $118,700 - $243,700

About The Position

Deloitte’s Audit and Assurance business is building an AI-enabled audit and uses machine learning and artificial intelligence to improve audit quality and provide deeper insights to clients. The Lead AI and Data Science Engineer II will lead technical work on data science projects and the development of AI and machine learning solutions, from research through production deployment and ongoing development. Current project areas include generative AI, prompt engineering, large language models, agentic systems, anomaly detection, clustering, and knowledge graphs.

The role works closely with audit subject matter experts, product teams, and software developers to define use cases and technical solutions and bring them to production. It includes managing and mentoring junior and senior data scientists, guiding independent research, and engaging with stakeholders with varying levels of machine learning experience. The successful candidate will lead rigorous data science work, oversee the development and deployment lifecycle, architect ML pipelines, and contribute high-quality production-ready code.

The position is listed in Boston, Massachusetts. The candidate must live within commuting distance of the assigned office and be able to commute daily if required. Work may take place alongside colleagues in a Deloitte office, at a client site, and/or virtually, depending on team and business expectations. Travel may be up to 25% on average.

Requirements

• Bachelor’s degree in a related field.
• At least 6 years of relevant industry experience designing, developing, and deploying machine learning models.
• Experience serving as technical lead for multiple project teams simultaneously.
• Expert understanding of the state of the art in at least two artificial intelligence fields, such as NLP and generative AI, probabilistic graphical models, time-series analysis, or weak supervised learning.
• Understanding of large language models, prompt engineering, and the use of evaluations in development and validation.
• Experience mentoring, training, and developing junior team members, including experience with employee performance reviews.
• Expert understanding of Python and other common programming languages.
• Demonstrated ability to lead the design and implementation of maintainable and scalable machine learning solutions throughout the development lifecycle.
• Extensive experience with common machine learning and deep learning frameworks, such as TensorFlow, PyTorch, OpenAI, and LangChain.
• Extensive experience with at least one cloud ecosystem: Azure, GCP, or AWS.
• Experience in an Agile working environment and with at least one related project management tool, such as Azure DevOps or Jira.
• Demonstrated ability to write high-quality, production-ready code that is readable, well-tested, well-documented, and uses well-designed APIs.
• Ability to develop novel machine learning methods beyond assembling existing open-source code and to solve complex problems.
• Solid understanding of Docker, Jenkins, Kubernetes, and other DevOps tools.
• Ability to reside within commuting distance of the assigned office and commute daily if required.
• Ability to co-locate with colleagues in a Deloitte office, at a client site, and/or virtually, according to team and business expectations.
• Ability to travel up to 25% on average, depending on work and clients served.
• Ability to work independently and collaboratively.
• Effective written and verbal communication skills.
• Meticulous attention to detail and quality of work.
• Ability to build and sustain professional relationships.
• Ability to lead projects or workstreams.
• Ability to manage and prioritize multiple tasks in a fast-paced, dynamic environment.
• Strong interpersonal skills and professional demeanor.
• Ability to meet deadlines.
• Ability to mentor others and provide clear guidance.

Nice To Haves

• At least 10 years of industry experience leading the design, development, and deployment of machine learning models.
• PhD in a quantitative field such as computer science, engineering, mathematics, physics, machine learning, or statistics.
• Prior scientific publications and an outstanding academic track record evidenced by top-tier publications.
• Strong project management and delivery experience, including budget oversight, project-team staffing, and time management.
• Extensive experience with Microsoft Azure, including machine learning certification.
• Experience with machine learning pipelines such as Azure ML or Databricks.
• Experience with ML Ops and related governance processes, particularly in a regulated industry.
• Strong presentation skills using Microsoft Office tools such as Visio and PowerPoint.
• Understanding of capital markets and the role of public accounting firms.

Responsibilities

• Lead rigorous data science work within the assigned workstream and manage or supervise junior resources throughout the data science development and deployment lifecycle.
• Collaborate with subject matter experts to understand business problems and define and refine technical solutions.
• Design and manage project plans, metrics, and objectives and key results that support the group's AI-enabled audit mission.
• Identify and communicate risks arising during the development lifecycle.
• Stay current with developments in data science and identify opportunities to apply new techniques.
• Mentor junior and senior data scientists, including providing regular feedback and staff touchpoints.
• Architect machine learning pipelines and contribute readable, well-tested, production-ready code with well-designed APIs.
• Lead technical aspects of data science projects and development of AI and machine learning solutions.
• Coordinate with audit subject matter experts, product teams, and software developers to develop use case requirements and bring solutions into production.
• Manage data scientists in completing the work required to develop and deploy production-level machine learning solutions.
• Perform or guide independent research and work with stakeholders with differing levels of machine learning experience.

Benefits

• Employees are offered a broad range of benefits; specific benefits are not enumerated in the posting.
• Eligible employees may participate in a discretionary annual incentive program, subject to program rules and factors including individual and organizational performance.
• Professional development opportunities include on-the-job learning, formal development programs, leadership opportunities, and mentorship.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior