Senior Director of Data Science

Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, Sam Altman, John Doerr, Spark Capital, SV Angel Growth, and others. 

You can read more at the following links:

• Our Vision for AI in Pharma
• Our Current Drug Portfolio
• Our Technology & Platform

At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently.

Formation Bio is seeking a highly skilled and experienced Senior Data Science Directorto join our dynamic team. This critical role will report to the head of Biometrics and will be responsible for leading and developing our data science team and strategy, driving impactful data-driven initiatives, and leveraging data to advance our drug development processes. We aim to build integrated predictive modeling capabilities, including for toxicology and efficacy, to significantly improve drug development efficiency and increase the probability of success. 

• Leadership and Team Development:
• Build and lead a high-performing data science team.
• Mentor and develop team members, fostering a culture of innovation and collaboration.
• Define and implement the data science strategy in alignment with company objectives.
• Strategic Data Utilization:
• Develop and execute strategies to maximize the value of data.
• Promote and integrate predictive analytics and advanced data science techniques into the drug development processes.
• Technical Guidance and Innovation:
• Provide deep technical expertise and mentorship to the data science team.
• Ensure the adoption of cutting-edge analytical methods and technologies.
• Drive the development and deployment of machine learning models and AI solutions in collaborations with internal tech teams.
• Cross-Functional Collaboration:
• Work closely with development and tech teams to facilitate data-driven decision-making.
• Collaborate with internal and external stakeholders to stay updated on emerging trends and technologies in data science.
• Data Governance and Quality:
• Ensure data quality, integrity, and security.
• Establish best practices for data management and analytics.
• Project Management:
• Drive end-to-end data science projects, ensure timely delivery and high impact.
• Manage stakeholder expectations and communicate complex data science concepts to non-technical audiences.

• Education:
• PhD in Data Science, Computer Science, Statistics, Mathematics, Life Sciences or a related field.
• Experience:
• 8+ years of experience in data science or related disciplines within the pharmaceutical industry, particularly in drug discovery and development.
• Proven experience in leading and managing data science teams.
• Strong track record of delivering impactful data science projects.
• Technical Skills:
• Drug Development Expertise: Excellent understanding of drug development processes, including preclinical and clinical stages, regulatory requirements, and the pharmaceutical industry's unique challenges and opportunities.
• Programming Proficiency: Advanced proficiency in programming languages such as Python, R, or Scala, with the ability to write clean, efficient, and scalable code.
• Machine Learning Expertise: Deep expertise in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn, including experience in developing, training, and deploying machine learning models.
• Big Data Technologies: Extensive experience with big data technologies such as Hadoop and Spark, including data processing, management, and analysis at scale.
• Analytical and Statistical Skills: Strong analytical and statistical skills, including knowledge of advanced statistical methods, data analysis techniques, and quantitative modeling.
• Data Management: Experience in data governance, data quality, data integrity, and data security best practices, ensuring robust data management processes.
• Technical Leadership: Proven ability to provide technical leadership and mentorship, guiding the team in adopting cutting-edge analytical methods and technologies.
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• Preferred Qualifications:
• Proven experience in cultivating relationships and influencing across various functions to drive success.
• Demonstrated success in driving technology transformation by collaborating with multiple stakeholders to align with business objectives and achieve positive outcomes
• Possess a growth mindset and thrive in ambiguity