Sr. Data Scientist, Technology Development Data Analytics

Cabaletta Bio•Philadelphia, PA

4d•Hybrid

About The Position

Cabaletta Bio (Nasdaq: CABA) is a late-stage clinical biotechnology company focused on developing and launching curative targeted cell therapies designed specifically for patients with autoimmune diseases. The CABA™ platform encompasses two complementary strategies which aim to advance the discovery and development of engineered T cell therapies with the potential to become deep and durable, perhaps curative, treatments for a broad range of autoimmune diseases. The lead CARTA (Chimeric Antigen Receptor T cells for Autoimmunity) strategy is prioritizing the development of rese-cel, a 4-1BB-containing fully human CD19-CAR T cell investigational therapy. Rese-cel is currently being evaluated in the RESET™ (REstoring SElf-Tolerance) clinical development program spanning multiple therapeutic areas, including rheumatology, neurology and dermatology. Cabaletta Bio’s headquarters and labs are located in Philadelphia, PA. For more information, please visit www.cabalettabio.com and connect with us on LinkedIn. Uniquely Differentiated. Rapid. Elegant. At Cabaletta, we are driven by the shared mission of developing cures, where a patients’ own cells are used to fight disease. We are building a culture grounded in the knowledge that successful cures can be achieved for patients if every member of the Cabaletta is focused on the success of the team. To nurture this, we make an active commitment to the well-being and continuous growth of each employee who joins the team. In this way, we are not only working to improve the lives of patients, but of everyone involved. #CabalettaCrew. We’re proud to be a Great Place to Work-Certified™ company! #GPTWcertified Check out what our employees say makes working here so great: Working at Cabaletta Bio Inc | Great Place to Work® About the Position : We are seeking a highly motivated and collaborative Sr. Data Scientist, Technical Development Data Analytics to join our Technical Development organization within a growing biotechnology/pharmaceutical company. This individual will help build and advance data science and data-driven capabilities across CMC, by applying scientific, statistical, and computational approaches to solve complex development and manufacturing challenges. The successful candidate will work at the intersection of CMC science and data analytics, partnering with Process Development, Analytical Development, Manufacturing, Quality, Supply Chain, and other cross-functional teams to integrate and analyze data, identify trends and relationships, and translate complex datasets into actionable scientific insights. We are looking for a data scientist with a strong scientific foundation and a demonstrated passion for working with data. We value scientific curiosity, learning agility, initiative, integrity, organization, communication, and motivation to develop new quantitative and computational capabilities. This role is well-suited for an individual who enjoys solving open-ended problems, is comfortable operating with ambiguity, and is excited about helping build new capabilities within Technical Development.

Requirements

Ph.D. or M.S. in Data Science, Statistics, Computer Science, Bioinformatics, or another relevant scientific, engineering, computational, or quantitative discipline.
2+ years of relevant industry experience (with a Ph.D.) or 5+ years (with an M.S.) is preferred, though candidates with equivalent demonstrated experience are encouraged to apply.
Demonstrated experience using data to address complex scientific or technical problems.
Strong scientific and quantitative problem-solving skills, with the ability to translate complex or ambiguous questions into structured analytical approaches.
Experience with statistical analysis, experimental design, data visualization, and/or analysis of complex scientific datasets.
Experience with, or demonstrated ability and motivation to learn, analytical and computational tools such as JMP, Python, R, SQL, Spotfire, Power BI, Tableau, or equivalent platforms.
Highly organized, with demonstrated ability to independently manage multiple analyses, datasets, priorities, and projects.
Strong interpersonal, written, and verbal communication skills, with demonstrated ability to collaborate effectively across scientific and functional disciplines.
Demonstrated initiative, ownership, and motivation to build new capabilities and solve problems beyond established approaches.

Nice To Haves

Experience with Design of Experiments (DoE), continued process verification (CPV), or statistical process control (SPC) is a plus.
Experience within biotechnology, pharmaceutical development, biologics, cell and gene therapy, GxP/regulated manufacturing environments, or other advanced therapeutic modalities is preferred.

Responsibilities

Partner with CMC subject matter experts to identify scientific and technical questions that can be addressed through data science, data integration, visualization, statistical analysis, and modeling.
Integrate and analyze data across process development, analytical development, manufacturing, raw materials, and product quality to improve process and product understanding.
Develop intuitive visualizations, dashboards, and analytical workflows that enable scientists and technical leaders to efficiently explore data, identify trends, and make informed decisions.
Help establish scalable and reproducible approaches for organizing, integrating, analyzing, and visualizing CMC data from multiple internal and external sources.
Apply and continue to develop capabilities in statistical and computational tools such as JMP, Python, R, SQL, Spotfire, Power BI, or similar platforms.
Explore opportunities to apply advanced analytics, automation, machine learning, and emerging AI-enabled approaches to relevant CMC scientific and operational challenges.
Independently lead data-focused projects from problem definition and data assessment through analysis, interpretation, visualization, and communication of conclusions.
Work effectively with complex and imperfect datasets and bring structure to scientific questions where the analytical approach or solution may not initially be well defined.
Clearly communicate analytical approaches, assumptions, limitations, and conclusions to technical and non-technical stakeholders.
Develop reusable analytical workflows, tools, and best practices that improve efficiency, consistency, and data accessibility across Technical Development.
Demonstrate scientific integrity, actively seek and incorporate feedback, and collaborate effectively across functions in an environment of scientific curiosity, continuous learning, accountability, and open communication.
Other related duties, as assigned