Data Scientist role emphasizing business insights and collaboration in insurance analytics. Involves working with clients and analyzing data for problem solving in various functional areas.
About the role
- Data Science Manager leading data scientists and analytics in pharmaceutical life sciences. Collaborating with teams to innovate and improve healthcare outcomes using AI techniques.
Responsibilities
- 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.
Requirements
- 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.
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