Director, Applied Data Science

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

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.