Data Scientist Engineer – SFL Scientific

Deloitte•Tampa, FL

140d•$95,600 - $188,400•Hybrid

About The Position

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 Scientist to collaborate directly with clients to design and develop novel projects and solutions. Join a rapidly growing team of professionals working to build a world-class data science practice focused on solving complex and R&D problems.

Requirements

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 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
Master’s or Ph.D. in a relevant STEM field (Data Science, Computer Science, Engineering, Physics, Mathematics, etc.)
2+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision)
2+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments
2+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Triton, RAPIDs, Kubeflow, and MLflow
2+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads
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

Nice To Haves

2+ years of experience working in a client-facing, consulting environment
1+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions
1+ year of experience with LLM/GenAI use cases and developing RAG solutions, agent-based tools and services, and GenAI frameworks (i.e., LangChain, LangGraph, MCP, etc.)
1+ year of experience with AWS Sagemaker or AWS ML Studio

Responsibilities

Define data strategy, drive technical development, and help create the next generation of tools, products, and AI services.
Work closely with clients to understand their data sets, strategy, and operational requirements, to drive exploratory data and use case analysis and design long-term solutions.
Guide clients with high autonomy in AI strategy and development, including understanding organizational needs, performing exploratory data analysis, building and validating models, and deploying models into production.
Participate in client initiatives to deliver AI/ML solutions, including providing thought leadership, long-term maintenance, and AI strategy objectives.
Research and implement novel machine learning approaches, including advancing state-of-the-art training, solution design, network design, and hardware optimization.
Validate AI models and algorithm via code reviews, unit, and integration tests.
Support prioritization of project performance and model development and ensure AI solutions are delivered to maximize business impact and new initiatives.
Collaborate with data engineers, data scientists, project managers, and business teams to make sure delivery and presentations align with business objectives.