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Data Scientist

Company: Takeda
Location: Cambridge
Posted on: September 16, 2020

Job Description:

By clicking the button, I understand that my employment application process with Takeda will commence and that I agree with Takeda's Privacy Notice, Privacy Policy and Terms of Use. Job Description Takeda is looking for a Data Scientist to join our Data Engineering and Artificial Intelligence team. We are looking for a Data Scientist who can use their Machine Learning, Deep Learning, Data Wrangling and Presentation skills to help deliver insights for our most difficult questions. You will work with the rest of the team to enable Takeda to continue its journey of data maturity, delivering outputs while educating others. You will be helping to solve some of the biggest question at Takeda and for healthcare in general. Are you looking for a patient-focused, innovation-driven company that will inspire you and empower you to shine? Join us as a Data Scientist in our Cambridge, MA location. POSITION OBJECTIVES - machine learning, deep learning and other advanced techniques while performing Data Analysis engagements. This is against structured and un-structured data sets, at small and large scale. - Independently perform complex analysis using modern Data Science techniques against structured or unstructured data to generate insights. - Provide mentorship to other Data Engineers, Data Scientists and Data Specialists across R & D and Vaccines at Takeda as we elevate our data IQ across the organization. - Deliver critical analysis against Takeda's toughest data problems to give us critical insight to the organization's largest questions. POSITION ACCOUNTABILITIES - Perform machine learning, deep learning and other advanced data techniques at a level of quality that can be defended to peers across organizations. - Introduce novel and state-of-the-art computational techniques to other teams and scientists to improve capabilities for data analysis with the purpose of deriving better insights from available datasets. - Understanding and usage of different Supervised and Unsupervised learning techniques, their biases, how and when to apply them and which methods are the best for a particular analysis. - Ability to wrangle raw data sets into a format that can have advanced methods applied against the resulting data. - Work independently to solve difficult technology and data problems. - Demonstrate usage of advanced tooling and techniques to other technical organizations throughout the company. Required EDUCATION, BEHAVIORAL COMPETENCIES AND SKILLS - Master's Degree or PhD in Computer Science, Data Science or equivalent - 3+ years' experience or a PhD and relevant project / coursework - Expertise with the Application of Machine Learning and / or Deep Learning - Up-to-date knowledge of data wrangling and analysis technologies - Experience with Spark - Ability to manipulate voluminous data with different degree of structuring across disparate sources to build and communicate actionable insights for internal or external parties - Possesses strong personal skills to portray information - Ability to work in an agile and rapid changing environment with high quality deliverables - Experience with two of the following languages Python, R, Java or Scala - Experience with deep learning frameworks TensorFlow, MX Net - Working knowledge of SQL and NoSQL datastores Preferred - Experience in a scientific environment - Experience with Reinforcement Learning What Takeda Can Offer You - 401(k) with company match and Annual Retirement Contribution Plan - Tuition reimbursement Company match of charitable contributions - Health & Wellness programs including onsite flu shots and health screenings - Generous time off for vacation and the option to purchase additional vacation days - Community Outreach Programs Empowering Our People to Shine Discover more at No Phone Calls or Recruiters Please. Locations Cambridge, MA Worker Type Employee Worker Sub-Type Regular Time Type Full time

Keywords: Takeda, Cambridge , Data Scientist, Other , Cambridge, Massachusetts

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