Job Title: Senior Data Scientist
Location: Watertown, MA (Onsite)

Role Description

Digital Biology is seeking a Senior/Principal Data Scientist to play a pivotal role in developing analysis pipelines and scientist-facing tools that empower data-driven decision-making. This role will work closely with Engineering and Discovery Scientists to develop scalable, automated workflows that streamline NGS, imaging, and multi-modal data analysis.

You will be responsible for building and running high-performance computational pipelines, developing and applying metrics and statistical decision frameworks, and building user-friendly scientist interfaces that enable scientists to visualize, interpret, and act on complex datasets with precision. In this role, you will work closely with scientists developing our high-throughput screening platform for biological T cell activators, using statistical methods to prioritize hits from library-based functional screens, based on NGS, image, and other data sources. You will also work closely with our engineering team to define and implement infrastructure to support data analysis and scientist interfaces. Finally, you will work closely with our CTO and our other computational scientists and engineers to onboard new capabilities that advance data-driven engineering of multifunctional biologics with desired functional properties.

Your contributions will be critical in driving discovery insights, optimizing biologic candidates, and accelerating therapeutic development.

This is an exciting opportunity to be a key technical leader at the intersection of data science, engineering, and biology, shaping the analytical infrastructure that powers next-generation biologics discovery.

Key Responsibilities

• Work closely with discovery scientists to define analytical needs, building customized workflows that accelerate target discovery and biologic optimization.
• Develop, run, and interpret scalable analysis pipelines for NGS and multi-modal data.
• Design and implement intuitive data visualization and scientist-facing tools.
• Collaborate with engineering to optimize data infrastructure, ensuring efficient storage, retrieval, integration, and processing of large-scale biological datasets.
• Integrate machine learning and statistical methods to extract meaningful patterns from high-throughput screening data.
• Enhance automation and reproducibility of computational workflows, promoting seamless integration with laboratory operations.
• Drive best practices for data integrity, quality control, and scientific reproducibility, ensuring that data-driven decisions are rigorous and impactful.
• Manage team of computational scientists, fostering a collaborative and growth-oriented environment.
• Ensure clear, well-structured documentation of analysis pipelines, methodologies, and key insights, enabling reproducibility and seamless knowledge transfer.
• Communicate findings effectively through reports, dashboards, and presentations, translating complex data into actionable insights for scientists and leadership.

Who you are

• You are a highly technical data scientist who thrives at the intersection of computation and biology. You have a strong engineering mindset, enjoy building scalable, automated analysis pipelines, and are passionate about developing scientist-friendly tools that unlock deeper insights from biological data.

Qualifications

• PhD in Computational Biology, Bioinformatics, Data Science, or a related field, with 5+ years of industry or postdoctoral experience.
• Strong understanding of statistics, with a proven track record of applying core principles to analysis of biological data.
• Fluency in Python, with experience building data pipelines and visualization tools.
• Experience applying software engineering best practices to scientific analysis, especially code review and version control (Git).
• Strong background in analyzing NGS data.
• Proven success in managing and mentoring bioinformatics scientists.
• Experience working with engineers to design and optimize data infrastructure for large-scale biological datasets.
• Familiarity with cloud computing environments, workflow automation, and database access and management.
• Exceptional communication and collaboration skills, with the ability to translate scientific needs into computational solutions.
• Passion for cutting-edge science.

Preferred Qualifications

• Industry experience in a fast-paced startup environment, working in cross-functional teams.
• Experience in analyzing high-resolution image data.
• Experience integrating multi-modal datasets, including sequencing, imaging, and functional profiling data.
• Experience with SQL databases.
• Fluency in R.

At Digital Biology, we believe that diverse perspectives drive scientific breakthroughs. We welcome applicants from all backgrounds and are committed to fostering an inclusive, innovative team environment.