Job Description
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments, we push the boundaries of what is possible to bring life-changing therapies to patients worldwide. Objective / Purpose: The Associate Scientist will play a critical role in advancing high-throughput mass spectrometry screening and iterative Design–Make–Test–Analyze (DMTA) activities across small and large molecule programs. Operating within fully automated, integrated laboratory systems, this individual will develop and execute robust bioanalytical assays that generate high-quality, decision-enabling data for small and large molecule discovery. With strong expertise in statistical analysis to assess assay robustness and data quality, the Associate Scientist will ensure rigor, reproducibility, and efficiency across programs. Importantly, this role will play a key part in Takeda’s “Lab of the Future” initiative, driving implementation of highly efficient, AI-integrated DMTA cycles that accelerate innovation and enhance data-driven discovery. This role contributes to critical function delivery: Accelerates Discovery Through Automation & AI Integration: Implements and operates fully automated, end-to-end assay workflows integrated with AI-enabled analytics to increase throughput, reduce variability, and shorten DMTA cycle times. Ensures Data Quality & Scientific Rigor: Applies statistical methodologies to evaluate assay performance (e.g., Z’, variability metrics, curve-fit confidence) and ensures high-integrity data that directly informs compound progression and portfolio decisions. Drives Cross-Functional Impact: Partners closely with DMPK, medicinal chemistry, data sciences, and early discovery teams to translate assay data into actionable insights, supporting timely and informed advancement of discovery programs. Accountabilities: Develop, miniaturize, optimize, and validate robust high-throughput MS workflows, with a primary focus on acoustic MS, RapidFire MS, MALDI-MS or similar platforms for small and large molecule biotherapeutic lead profiling. Generate high-quality, reproducible data to enable informed decision-making within iterative Design–Make–Test–Analyze (DMTA) cycles. Design and execute quantitative and qualitative bioanalytical assays at 384- or 1536-well scale Perform and ensure timely execution of MS detection assays and communicate results effectively to program teams. Apply rigorous statistical analysis, curve fitting, and data visualization tools to interpret complex datasets. Utilize automation platforms and laboratory instrumentation to improve assay throughput, consistency, and efficiency. Collaborate closely with cross-functional teams including DMPK, medicinal chemistry, data sciences, and early discovery to drive project progression. Interpret, summarize, and present research findings at internal meetings and external scientific conferences as needed. Sustain a high-performing and reliable laboratory environment by rigorously applying quality control standards, executing preventative maintenance of instrumentation, and ensuring strict adherence to established standard operating procedures (SOPs). Familiarity with LIMS/ELN systems. Education & Competencies (Technical and Behavioral): Master’s degree in Analytical Chemistry, Biochemistry, Pharmaceutical Sciences or related discipline with 3+ years OR Bachelor’s degree with 5+ years of relevant industry experience in drug discovery (pharma/biotech). Demonstrated expertise in High-throughput MS platforms (Acoustic MS, RapidFire MS, MALDI-MS or other platforms) Method development, optimization, troubleshooting and routine operation Experience working within DMTA-driven discovery workflows. Proficiency with MS data analysis tools and software; experience with scripting or data handling (e.g., Python, R, Spotfire) is a plus. Familiarity with laboratory automation systems. Excellent organizational and communication skills. Proven experience in developing and/or evaluating novel small molecule and biologics. Demonstrated ability to work independently and collaboratively in a highly matrixed, cross-functional environment while managing multiple priorities. Stays current with emerging scientific literature, competitive landscapes, and innovat