US E-Consulting-Deep Learning Data Science Manager, Specialist Master-S&A Strategy SFL Scientific DSM-KP (182712) [PATH B]

Deloitte US
Philadelphia, PA Full Time
POSTED ON 5/30/2024

Deep Learning Data Science Manager

SFL Scientific, a Deloitte Business practice brings together several key capabilities to architect integrated programs that transform our clients' businesses, including Strategic Growth Transformation, Transformation Strategy & Design, Technology Strategy & Business Transformation, and AI & Data Strategy.

Professionals will serve as trusted advisors to our clients, working with them to make clear data-driven choices about where to play and how to win – ultimately driving growth and enterprise value.

We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, energy, and other sectors.

Recruiting for this role ends on 5/31/2024.

Work you’ll do

As a Data Science Manager at SFL Scientific, a Deloitte Business, you’ll manage a team of developers across project execution and R&D efforts. 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 applications as diverse as healthcare, medical imaging, autonomous systems, and embedded & edge-AI. 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 in order to meet each clients’ unique requirements
  • Engage and guide 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
  • Lead in the research and adoption of industry best practices for validation of models; support best delivery practices, including validation, code review, unit, and integration tests
  • Present to key stakeholders, including dataset findings and solution infrastructure, hardware, software, cloud, and deployment, etc.
  • Mentor, motivate and coach junior data scientists on technical best practices and inspire professional development

The Team

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. 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:

  • Master’s or Ph.D 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
  • Excellent verbal and written communication skills and experience in a client-facing or team management role is preferred 
  • 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 $151,800 to $253,000.

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.

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