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Job DescriptionAbout the role:
The Principal Data Scientist applies strong expertise in artificial intelligence through the use of machine learning, data mining, and information retrieval to design, prototype and build next generation advanced analytics engines and services. This role invites you to
identify the value generation within the data that can be gained in business processes and propose methods to gain further value. You will collaborate with business partners to define the technical problem statement and hypothesis to test, develop efficient and accurate analytical models that mimic business decisions, and incorporate them into analytical data products or tools with the support of cross-functional teams.
How you will contribute:
Collaborate with business partners to develop novel ways to meet objectives utilizing cutting-edge techniques and toolsEffectively communicate the analytics approach and how it will meet and address objectives to business partnersAdvocate and educate on the value of data-driven decision making focusing on the “how and why” of solving problemsLead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts, and developersCreate repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytic data productsEngineer features by using your business acumen to find new ways to combine disparate internal and external data sourcesShare your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods, and standardsCollaborate, coach, and learn with a growing team of experienced Data ScientistsStay connected with external sources of ideas through conferences and community engagementsTranslate data science, artificial intelligence and machine learning trends and technologies into executionWhat you bring to Takeda:
An advanced degree is required (Master/MBA and/or PhD), e.g. in sciences (such as computer science), Technology, Engineering, Mathematics.Experience in applying and executing Digital/Big Data Analytics/ Artificial Intelligence/Machine Learning, Machine Learning algorithms, statistics, process mining and stochastic models.Fluency in EnglishA firm grasp of industry, scientific, AI, machine learning and data science trends and market conditionsMotivation to develop solutions that enhance the quality of life for patientsAbility to interface with international stakeholders and to connect internal and external data analytics experts of both academia and industryPython or R proficiency working with Data Frames Writing complex SQL queries Machine Learning fundamentals Creating new features by merging and transforming disparate internal & external data sets Big Data technologies (e.g., Hadoop, Spark, Dataiku, DataRobot, DataBricks, Cloud AI platforms) Deployment, monitoring, maintenance, and enhancement of models desired Data modeling and data visualization tools.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.
Empowering our people to shine:
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, or any other characteristic protected by law.
LocationsZurich, SwitzerlandWorker TypeEmployeeWorker Sub-TypeRegularTime Type80-100%