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About the Role

We are seeking a highly motivated and collaborative Sr. Data Scientist, Technical Development Data Analytics to join our Technical Development organization. This individual will apply scientific, statistical, and computational approaches to solve complex development and manufacturing challenges by building and advancing data science and data-driven capabilities across CMC. The role involves working at the intersection of CMC science and data analytics, partnering with cross-functional teams to integrate and analyze data, identify trends, and translate complex datasets into actionable scientific insights. We are looking for a data scientist with a strong scientific foundation and a passion for data, who enjoys solving open-ended problems and is comfortable with ambiguity.

Responsibilities

Partner with CMC subject matter experts to identify scientific and technical questions addressable 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 enhance process and product understanding.
Develop visualizations, dashboards, and analytical workflows for efficient data exploration, trend identification, and decision-making.
Establish scalable and reproducible methods for organizing, integrating, analyzing, and visualizing CMC data from multiple sources.
Apply and 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 approaches to CMC challenges.
Independently lead data-focused projects from problem definition to conclusion communication.
Work effectively with complex and imperfect datasets, structuring scientific questions with initially undefined analytical approaches.
Clearly communicate analytical approaches, assumptions, limitations, and conclusions to technical and non-technical stakeholders.
Develop reusable analytical workflows, tools, and best practices to improve efficiency, consistency, and data accessibility.
Demonstrate scientific integrity, seek and incorporate feedback, and collaborate effectively across functions.
Perform other related duties as assigned.

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

Skills

Data Science
Data Integration
Data Visualization
Statistical Analysis
Modeling
JMP
Python
R
SQL
Spotfire
Power BI
Tableau
Design of Experiments (DoE)
Continued Process Verification (CPV)
Statistical Process Control (SPC)
Machine Learning
AI

Location

Hybrid/Philadelphia

Work Type

Hybrid

Experience Level

Senior
2+ years with Ph.D.
5+ years with M.S.

Education Level

Ph.D.
M.S.

Benefits

Competitive benefits
PTO
Stock option plans

About the Company

Cabaletta Bio is a late-stage clinical biotechnology company focused on developing and launching curative targeted cell therapies for autoimmune diseases.
The CABA™ platform uses two complementary strategies to advance engineered T cell therapies.
The lead CARTA strategy is developing rese-cel, a CD19-CAR T cell investigational therapy, evaluated in the RESET™ clinical development program.
Cabaletta Bio’s headquarters and labs are located in Philadelphia, PA.
The company is driven by the mission of developing cures using a patient's own cells to fight disease.
Cabaletta is building a culture focused on team success and committed to employee well-being and continuous growth.
The company is Great Place to Work-Certified™.
The name Cabaletta is derived from an operatic term representing a rapid, repetitive, and technically challenging section of an aria, reflecting the company's aim for rapid and repetitive product development.

Equal Opportunity

Cabaletta Bio is an equal opportunity employer. We do not discriminate on the basis of race, color, gender, gender identity, sexual orientation, age, religion, national or ethnic origin, disability, protected veteran status or any other basis protected by applicable law.