Logo
Takeda

Data Scientist

Takeda, Lexington, Massachusetts, United States, 02173


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

About the role:

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 four therapeutic areas and other targeted investments, we push the boundaries of what is possible in order to bring life-changing therapies to patients worldwide.Join Takeda as a Data Scientist where you will work with drug product scientists, device engineers, test engineers, and process development experts to develop and validate computational techniques and simulations to model and predict the behavior and interaction of biological, chemical, and physical systems. You will also support digitalization of business and quality processes. As part of the Drug Product and Device Development (DPDD) team, you will report to Director, Commercial Device Engineering. DPDD develops Drug, Device, and Combination products in a sustainable and cost-effective process.You will have an innovative mindset, able to leverage your experience with advanced data analytics, In Silico technology, Artificial Intelligence, Machine Learning, Deep Learning, and Digitalization techniques to support combination product development and lifecycle management.How you will contribute:

You will lead the initiatives to integrate the In Silico and automation approaches into the combination product development, risk management, manufacturing and post market lifecycle management.You will partner with data scientists to develop an infrastructure and processes for the contextualization, organization, visualization, and storage of the generated data, to enable autonomous and intelligent process development. Identify and convert physical activities in development and lifecycle to digital platforms.You will have deep experience processing large data sets and applying advanced methods to visualize and extract value from them. You will have experience developing workflows for data collection using a wide range of automation tools, from traditional platforms to the use and development of complex software solutions. You will have knowledge of multiple process analytical technologies (PAT), Pharma 4.0 digital maturity models and systems, and testing and building simulation models. You will strive to improve our workflows to facilitate and accelerate process development, optimization, and understanding.You will be recognized as a technical resource/expert within DPDD and across Pharmaceutical Sciences and use technical expertise to contribute across multiple projects and drive technical/scientific strategy. You will collaborate closely with product development groups, digital and manufacturing based on pipeline needs and current trends in research. You will maintain and grow the department's strategic relationships with our outsourcing partners, academic collaborators, and pre-competitive consortia, as well as directing and managing outsourcing across a product platform, as appropriate.Document model development and validation processes, ensuring compliance with regulatory standards.Present findings and provide insights to stakeholders to inform decision-making processes.Stay updated with the latest advancements in data science, machine learning, and in-silico modeling techniques, incorporating novel automation technologies and industry trends as a key aspect of scientific strategy development.Ensure project management of all plans and projects within your responsibilities, linking all scientific efforts to company, program and functional goals.Identify topics for initiatives and lead local/global and cross-functional initiatives on behalf of senior staff.Represent Takeda and be an active member on pre-competitive collaborations with academic and industrial partners.May require approximately 10% travel.Minimum Requirements/Qualifications:

PhD in engineering or related pharmaceutical science.Masters degree in engineering or related pharmaceutical science and 6+ years relevant industry experience.Bachelors degree in engineering or related pharmaceutical science and 8+ years relevant industry experience.Extensive experience in the use of computational modeling and simulation in medical device or related areas.Proficiency in computational modeling software (FEA, CFD, etc.), and CAD software such as SolidWorks.Experience in Artificial Intelligence (AI) and Machine Learning (ML).Experience validating computational models.Ability to work independently and as part of a multidisciplinary team.Strong problem-solving skills and attention to detail.Excellent communication and presentation skills.Experience managing staff preferred.Sound knowledge of current Good Manufacturing Practices (cGMP).Previous experience contributing to regulatory filings, preferably experience will late-stage filings.Proven scientific track record through presentations at scientific conferences and publication of peer-reviewed manuscripts.More about us:

At Takeda, we are transforming patient care through the development of novel specialty pharmaceuticals and best in class patient support programs. Takeda is a patient-focused company that will inspire and empower you to grow through life-changing work.Certified as a Global Top Employer, Takeda offers stimulating careers, encourages innovation, and strives for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.This position is currently classified as "hybrid" in accordance with Takeda's Hybrid and Remote Work policy.Locations

Lexington, MAWorker Type

EmployeeWorker Sub-Type

RegularTime Type

Full time

#J-18808-Ljbffr