Data Scientist


Job Overview

A career with MilliporeSigma is an ongoing journey of discovery: our 57,000 people are shaping how the world lives, works and plays through next generation advancements in healthcare, life science and performance materials. For more than 350 years and across the world we have passionately pursued our curiosity to find novel and vibrant ways of enhancing the lives of others. MilliporeSigma is a business of Merck KGaA, Darmstadt, Germany.Your Role:The North America Research Sales Enablement team is looking to add a Data Scientist in our team who will support the North America Commercial Sales organization.  The role offers both an opportunity to develop sophisticated data models to help drive business growth as well as a strong focus on process improvement and efficiency gains to be leveraged in the organization. You will:Build, optimize and maintain conceptual and logical database models to be used for predictive and prescriptive modeling in the NA Research Commercial Sales organization.Develop database solutions to store and retrieve internal and external information to be used in data models.Optimize current systems and processes used by the NA Sales Enablement team for efficiency and effectivenessDesign conceptual and logical data models and flowcharts.Employ sophisticated analytics programs, machine learning and statistical methods within the data sets.Explore and examine data from a variety of angles to determine hidden weaknesses, trends and/or opportunities.Who You Are:Minimum Qualifications:BS in Statistics, Mathematics, Computer Science, or other quantitative disciplines.5+ years working with large datasets in a big data environment.Extensive knowledge and experience in at least three of the following areas: predictive statistical models, customer profiling, segmentation analysis, data mining, web mining, machine learning, statistics, databases, data warehousing, data processing (ETL).Experience with Python, R, and/or SQL.  Experience with big data platforms and visualization tools (e.g Tableau).Advanced skills in Microsoft Office (Excel, Word, PowerPoint) as well VBA and macros.Preferred Qualifications:Master’s degreeStrong attention to detail when identifying data relationships, trends and anomalies.Comfortable reporting results to both technical and non-technical audiences.Self-motivated with the ability to be productive in a fast-paced environment.Ability to work with people from various backgrounds/cultures.Strong interpersonal skills with the desire to share knowledge and skills.What we offer: With us, there are always opportunities to break new ground. We empower you to fulfil your ambitions, and our diverse businesses offer various career moves to seek new horizons. We trust you with responsibility early on and support you to draw your own career map that is responsive to your aspirations and priorities in life. Join us and bring your curiosity to life!Curious? Apply and find more information at The Company is an Equal Employment Opportunity employer. No employee or applicant for employment will be discriminated against on the basis of race, color, religion, age, sex, sexual orientation, national origin, ancestry, disability, military or veteran status, genetic information, gender identity, transgender status, marital status, or any other classification protected by applicable federal, state, or local law.  This policy of Equal Employment Opportunity applies to all policies and programs relating to recruitment and hiring, promotion, compensation, benefits, discipline, termination, and all other terms and conditions of employment. Any applicant or employee who believes they have been discriminated against by the Company or anyone acting on behalf of the Company must report any concerns to their Human Resources Business Partner, Legal, or Compliance immediately. The Company will not retaliate against any individual because they made a good faith report of discrimination. Req Id 208825 – Posted 08/14/2020 – United States – Massachusetts – Burlington – Commercial – Career Level (1) – full-time

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