Data Science Manager, Life Sciences & Healthcare – Sfl Scientific

Manager for a team developing AI/GenAI solutions in healthcare and life sciences, focusing on technical direction, strategy, and client engagement. Requires expertise in computer vision, NLP, time-series analysis, and graph neural networks.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. 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
  5. Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.

Skills

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, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.)
  • 6+ years of experience with traditional ML and deep learning

Other signals

  • AI/ML solutions
  • GenAI domains
  • computer vision
  • natural language processing (NLP)
  • time-series analysis
  • graph neural networks