Work Schedule

First Shift (Days)

Environmental Conditions

Office

Job Description

As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.

Location/Division Specific Information

The team focuses on commercial audience generation through audience segmentation, time-to-event analysis, recommendation engines, generative AI, and other forms of predictive modeling. You will work closely with experts throughout the company to develop tailored targeting strategies. Your work will be seen and used by fellow data scientists, collaborators within the business, sales representatives, and customers of Thermo Fisher. You will be expected to learn quickly and offer creative and effective solutions to novel challenges.

You will report to a member of the data science team and operate as a key asset within the Corporate Data Science Center of Excellence, a team comprised of data scientists, data engineers, business analysts, program/product managers, and others.

Key ResponsibilitiesIdentify and embed within business functions throughout the company with high data science potential.Move quickly to build proof of concepts, scalable solutions, and anything else required to drive business value quickly.Leverage modern tools and techniques to develop novel insights.Promote standard methodologies in the field, encompassing data warehousing, performance monitoring, and a balanced approach.Work with senior members to build novel audience-creation and targeting strategiesVoracious pursuit of knowledge and an unwavering dedication to the scientific process

Keys to Success:

EducationGraduate degree in a quantitative field, such as statistics, economics, mathematics, etc.ExperienceProven track record (3 to 6 years) applying industry standard data science tools to tackle previously unsolved problemsAbility to work independently with minimal day-to-day oversightKnowledge, Skills, AbilitiesExtensive knowledge and application of the scientific process in industryCommand of statistical topics, including distributions, hypothesis testing, and experiment design.Sophisticated technical proficiency in Python, R, SQL, and others.Proficiency with distributed computational frameworks, such as SparkFoundational understanding in digital marketing, sales operations, and key performance indicatorsFluent English both written and spoken is required.