Senior Staff Engineer – Modeling
| Company | Takeda |
|---|---|
| Location | Boston, MA, USA |
| Salary | $137000 – $215270 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s degree in Chemical Engineering or a related pharmaceutical science with 11+ years of relevant industry experience.
- Master’s degree in Chemical Engineering or a related pharmaceutical science with 9+ years of relevant industry experience.
- Ph.D. or postdoctoral fellowship in Chemical Engineering or a related pharmaceutical science with 3+ years of relevant industry experience.
- Strong knowledge and understanding of chemical reaction engineering and catalysis, with proven ability to demonstrate skills in these fields.
- Strong knowledge and understanding of transport phenomena and thermodynamics.
- Extended experience with commercially available reaction kinetic modeling software such as Ansys, ReactionLab, Dynochem, and gPROMS.
- Extended experience with commercially available software for computational fluid dynamics (CFD) modeling such as Ansys, Star CCM+, MStar CFD.
- Proficient in communicating and data collection from systems such as sensors, controllers, and industrial systems.
- Experience with Matlab, Python, R, SQL, and good coding practices.
Responsibilities
- Lead and contribute to the design, development, optimization, and scale-up of manufacturing processes for synthetic molecule drug substances using process modeling and simulation principles.
- Utilize advanced process modeling tools and digital twin functionalities, implementing model-based design of experiments for process characterization and risk assessment.
- Lead and develop experimental designs and workflows for model development, validation, and verification.
- Collaborates with cross-functional and external partners to develop and deploy digital twins of unit operations.
- Partner with Automation, Manufacturing, Process Engineers, and PAT experts to develop modeling and simulation (M&S) solutions that can be deployed across the global organization for in-silico process design, development, and optimization.
- Recommend, justify and implement *in silico* tools and an ‘*in-silico* first’ approach to process development.
- Contribute to the democratization of modeling and simulation tools & results within global SMPD.
- Develop project or significant technical strategy and leverages technical skill(s) as a resource/expert within the department.
- Recognized as a technical expert and resource within the function.
- Contribute significantly and independently to project work as well as the development of platforms, which may include multiple projects within functional area.
- Proactively analyze technical issues and coordinate potential resolutions with project team members based on model and simulation predictions.
- Review, interpret and communicate data cross functionally within pharmaceutical sciences and project teams.
- Significant technical responsibility for a project area/technical program within the department and potentially across Pharmaceutical sciences.
- Stay current in novel process modeling and simulation tools and platforms, identify process trends and defines/champions process strategy.
- Influence and support initiatives related to driving scientific and technical improvement within the function and potentially cross-functionally.
- Identify topics for initiatives and lead local/global initiatives on behalf of senior staff.
- Author relevant sections of regulatory documents, validation plans, reports and peer reviewed manuscripts.
- Identify vendors and build relationships to gain access to technologies as needed to deliver on pipeline and platform technology goals.
- Manage key vendor relationships across multiple projects as appropriate, and proactively affects resolution of issues arising at vendors.
- Represent Takeda and is an active member on pre-competitive collaborations with academic and industrial partners.
Preferred Qualifications
- Experience with common statistical methods, basic data science principles, and AI/ML methodologies.
- Hands-on experience in wet lab process development.
- Experience in multivariate analysis and Principal Component Analysis (PCA).
- Understanding of synthetic molecule process development activities.
- Understanding of current Good Manufacturing Practices (cGMP)