Manager- Data Science

We'll trust you to:

• Lead and mentor a team of data scientists, guiding 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.
• Develop advanced algorithms to solve problems of large dimensionality in a computationally efficient and statistically effective manner.
• Execute and manage projects demanding the application of advanced analytics techniques (e.g., descriptive/inferential statistics, machine learning, NLP, and Neural Networks) on large, unstructured data sets to identify key actionable insights.
• Lead client communications, and internal stakeholder conversations, and manage workstreams.
• Evaluate emerging datasets, business areas, and technologies.
• Participate and contribute to thought leadership through active innovation, research, and publication.

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.
• 6+ years of experience in data science, with a proven track record of delivering impactful solutions in the pharmaceutical and life sciences industry.
• Strong proficiency in machine learning, statistical analysis, and data manipulation using Python, R, or similar state-of-the-art tools. Experience in the development and deployment of large-scale products/solutions is preferred.
• 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 managing and mentoring a team of data scientists and collaborating with other stakeholders (consulting, IT, 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.