xilis
Next generation technologies for precision medicine.
organoids • precision medicine • oncology • cancer • tissue engineering
51 - 200
Senior Director of Data Science
July 30
🏡 Remote – New York
xilis
Next generation technologies for precision medicine.
organoids • precision medicine • oncology • cancer • tissue engineering
51 - 200
Description
• Lead and grow the data science team, setting strategic direction and fostering a culture of strong execution, scientific innovation, and industry-grade best practices. • Develop and implement advanced ML and computer vision solutions to analyze and interpret biological data, with a focus on cancer biology and microscopy image analysis • Oversee the end-to-end machine learning lifecycle, from ideation to production deployment • Collaborate with cross-functional teams of biologists, clinicians, and data scientists to identify opportunities for data-driven solutions in cancer research • Establish best practices for MLOps, ensuring scalable and maintainable AI/ML systems in a biological context • Stay current with the latest advancements in data science, AI, and computational biology • Drive data-informed decision-making across the organization, translating biological insights into actionable strategies
Requirements
• PhD in Computational Biology, Bioinformatics, Applied Mathematics, Computer Science or related field • 8+ years of industry experience in data science applied to biological problems, with at least 3 years in a leadership role • Strong background in biology, with significant experience or knowledge in cancer biology • Proven track record in developing and deploying ML and computer vision solutions for biological data analysis • Demonstrated ability to generate meaningful insights from complex biological datasets using ML tools • Strong understanding of MLOps practices and tools • Experience working with cloud platforms (AWS) for large-scale biological data processing • Experience working in a fast-paced biotech startup environment, delivering high-quality results under tight timelines • Excellent communication skills, able to bridge the gap between data science and biology teams
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