Data Science Manager, GenAI - SFL Scientific
- 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
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
- 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
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