Data Science Manager

We'll trust you to:

• Lead and mentor a team of data scientists, providing guidance and support in project execution, methodology selection, and professional development.
• Collaborate with stakeholders to define project objectives, deliverables, and success criteria, ensuring alignment with business goals and priorities.
• Design and implement advanced analytics solutions to address complex challenges in drug discovery, clinical development, and commercialization.
• Apply machine learning techniques, including deep learning and generative AI, to analyze diverse datasets (structured and unstructured) and generate actionable insights.
• Drive innovation by staying abreast of emerging trends, technologies, and best practices in data science and the pharmaceutical industry.
• Establish robust processes for data collection, preparation, and validation, ensuring the reliability and integrity of analytical models and findings.
• Communicate findings and recommendations to technical and non-technical stakeholders through clear, compelling visualizations, presentations, and reports.
• Collaborate with IT and data engineering teams to optimize data infrastructure and facilitate seamless integration of analytics solutions into existing systems.
• Participate and contribute to thought leadership through active innovation, research and publication.
• Own project management and provide guidance to project teams of junior team members.

You'll need to have:

• Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics) required; Ph.D. preferred.
• 9+ years of experience in data science, with a proven track record of delivering impactful solutions in the pharmaceutical and life sciences industry (Hands-on experience is preferred)
• Demonstrated success in managing data & analytics engagements in life sciences or healthcare industries. Preferred expertise in analytics related to drug commercialization (sales force analytics, omnichannel, attribution modeling etc.). Analytical Diversity and agility preferred
• Strong proficiency in machine learning, statistical analysis, and data manipulation using Python, or similar state of the art tools. Experience in development and deployment of large scale products/solutions is preferred.
• Experience working with cloud platforms such as AWS, Azure, or GCP, including deploying, managing, and optimizing cloud-based solutions.
• Experience with generative AI development and associated techniques, such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and RL (Reinforcement Learning), preferred.
• Demonstrated leadership skills, with experience in managing and mentoring a team of data scientists and collaborating with other stakeholders (consulting, IT, tech etc.)
• Excellent communication and collaboration skills, with the ability to translate complex technical concepts into clear, actionable insights for diverse audiences. Client management experience is a plus
• Strong problem-solving and critical-thinking abilities, with a research-oriented mindset and passion for tackling challenging problems, driving innovation in healthcare using ever evolving AI techniques.