Data Science Manager, Life Sciences & Healthcare - SFL Scientific at Deloitte
Raleigh, NC 27603, USA -
Full Time


Start Date

Immediate

Expiry Date

11 Sep, 25

Salary

241000.0

Posted On

12 Jun, 25

Experience

6 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Cloud, Validation, Computer Science, Nlp, Code Review, Aws, Professional Services, Prototyping, Keras, Training, Physics, Algorithm Development, Computer Vision, Data Engineering, Models, Mathematics, Software, Programming Languages, Hospital Operations

Industry

Information Technology/IT

Description

DATA SCIENCE MANAGER, HEALTHCARE & LIFE SCIENCES - SFL SCIENTIFIC

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, a Deloitte Business practice 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 and life sciences.
Recruiting for this role ends on 7/31/2025.

QUALIFICATIONS:

  • 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, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, 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 QUALIFICATIONS:

  • 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 for healthcare or life sciences
  • Experience in a client-facing role
  • Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
    Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
    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 $130,800 to $241,000.
    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
Responsibilities

As a Data Science Manager at SFL Scientific, a Deloitte Business, you will 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.

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 in healthcare, diagnostics, hospital operations, and more. Join us to expand your technical career through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

  • 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 healthcare 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 for an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for clinical and non-clinician 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
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