Director, Applied Data Science
Apr 2, 2025
Candidates local to Seattle are preferred, but remote applicants are welcome to apply. Candidates must reside in the United States.
Starting Salary Range: $214,000 - $238,000 annually
Exemption Status: Exempt
Location Expectations: Remote-Eligible
Role Description
At A-Alpha Bio, we’re on a mission to improve human health by unlocking the potential of protein-protein interactions – and we’re now seeking a seasoned Director of Applied Data Science to lead a team of skilled Data Scientists making the most of A-Alpha’s proprietary data platform and machine learning capabilities.
As a scientist, you’ll help unravel the intricacies of protein-protein interactions—both to power our in-house drug discovery pipeline and in collaboration with major biopharma partners.
As a strategist, you’ll collaborate closely with R&D, Business Development, and the executive team to navigate feasibility, bandwidth constraints, ownership, and action plans for cutting-edge computational workflows.
As a manager, you’ll coach, mentor, develop, and advocate for a team of world-class data scientists, helping every member of the team do their best work in an intellectually stimulating and highly technical environment.
Key Responsibilities
Grow and manage a high-performing team of data scientists working on computational analysis of many disparate internal and external projects.
Represent A-Alpha to external stakeholders by leading data science efforts for major partnerships.
Independently identify and pursue methodological improvements and new scientific objectives within areas of expertise.
Work closely with colleagues to maximize the impact of computational analysis for ongoing drug discovery and optimization campaigns.
Participate in the publication of research papers and filing of patents.
Perform other duties as assigned.
Qualifications & Experience
Required
PhD in a related field with 10+ years of experience and 5+ years of management experience; or an equivalent combination of education and experience.
Direct experience in statistical treatment of high-throughput biological data, as well as in the application of deep learning to high-throughput biological sequence data.
Familiarity with state-of-the-art machine learning techniques in at least one of the following areas: antibody or protein engineering, drug discovery, NGS-based assays, and/or synthetic biology.
Proven leadership in recruiting and managing high-performing teams of scientists and engineers in a cross-functional and fast-paced environment, with a history of maximizing and growing internal talent.
Ability and desire to contribute to applied data science as an expert individual contributor in addition to management duties.
Impressive technical track record at leading pharma/biotech companies.
Strong interpersonal, verbal/written communication, and problem-solving skills.
Preferred
Experience with contracting, business development, and alliance management in the context of pharma/biotech partnerships
Experience with the application of natural language processing techniques to high-throughput biological sequence data at scale.
Experience creating and maintaining deployment pipelines with CI/CD tools.
Expertise with Python, Pandas, Pytorch, and Amazon Web Services.
