Data Scientist Engineer - SFL Scientific
- 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
- 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
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. 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 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
- 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
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