Scientific Manager Jobs (NOW HIRING)

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

• Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
• Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
• Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
• Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
• Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
• Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
• Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
• Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
• Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

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 mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

• Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
• 6+ years of experience working in data science, data engineering, software engineering, or MLOps
• 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
• 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
• 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
• 4+ years of experience managing teams and delivering complex and critical projects
• Live within commuting distance to one of Deloitte's consulting offices
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
• Limited immigration sponsorship may be available

Preferred:

• Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
• Experience with developing and testing GenAI solutions
• Experience in a client-facing role or internal AI product development role
• Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations

The wage range for this role 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. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. 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 $155,600 to $306,800.

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.

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

• Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
• Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
• Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
• Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
• Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
• Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
• Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
• Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
• Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

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 mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

• Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
• 6+ years of experience working in data science, data engineering, software engineering, or MLOps
• 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
• 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
• 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNN...