Staff Scientist, Data Sciences

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

When you join us at Thermo Fisher Scientific, you’ll be part of an inquisitive team that shares your passion for exploration and discovery. With revenues of more than $40 billion and the largest investment in R&D in the industry, we give our people the resources and chances to create significant contributions to the world.

Staff Scientist, Data Sciences – Corporate/LPG-LCD

An opportunity exists for a Staff Scientist, Data Sciences in the Corporate Data Science team supporting the Laboratory Chemicals Division (LCD) of Thermo Fisher Scientific. This position offers the right candidate a key position in the Corporate Team supporting the Laboratory Products Group and will provide opportunities for career development and growth. The position has global coverage and will be based in Pittsburgh, PA, operating with a hybrid calendar (minimum 3 days onsite per week). You will report to a managing data scientist and be positioned on an existing team of several data scientists, analysts, and a program manager.

The Laboratory Chemicals Divisions (LCD) enables its customers by bringing chemistry to life! Scientific journeys begin with chemicals and end with life-enriching results. Our purpose is to deliver chemicals safely and efficiently, so that our customers can focus on results. Together, we will:

• Become the trusted partner for chemicals in the markets we serve
• Honor our commitments by consistently delivering results
• Become an admired business to work for, and a safe and exciting career destination for superior talent.

Collaborating with a dedicated team, you will gain insights into the intricate business challenges and transform them into operational frameworks and algorithms. These solutions will be presented to fellow analysts and business partners. There will be a continuous challenge to develop new analytic capabilities and improve existing ones on a wide variety of projects. The Staff Data Scientist will choose the approach taken.

How will you make an impact:

You will enable our customers to make the world healthier, cleaner, and safer by employing a cross section of machine learning and analytic processes to develop algorithms that will improve efficiency and drive revenue enabling growth for Thermo Fisher Scientific Chemicals division.

What will you do: Responsibilities

• Develops strategies and requirements to use artificial intelligence and automation to enhance business decisions.
• Quickly grasp the sophisticated business priorities and marketing objectives to translate them into algorithms and communicate the results to team members with varying degrees of technical background
• Collaborate closely with peers in Marketing, Portfolio Management, and Sales to identify key business needs and areas of opportunities and translate business questions into quantitative analyses.
• Proactively identify and evaluate growth opportunities to be translated as recommendations for our Commercial and Marketing teams.
• Develop visualization and key performance indexes to supervise effectiveness of marketing and guide marketing decisions.
• Proactively identify gaps and opportunities for sales and marketing teams and use data to generate leads and to drive revenue.
• Efficiently respond to requests for ad hoc analyses.
• Work with Marketing Analytics team to create reporting to drive desired business results.

How will you get here:

• Bachelor's Degree with 5 years of proven experience in data science, analytics, statistics, applied math or related OR Master’s Degree with 3 years of proven experience
• Business analytics required, pricing or marketing analytics experience a plus
• Proficiency in Python (or PySpark) and SQL
• AWS/Cloud Computing experience preferred
• Exposure to a variety of operating systems and computing platforms preferred
• Familiarity with available Open-Source solutions that will boost the team’s effectiveness preferred

Knowledge, Skills, Abilities:

• Extracting data from multiple sources, cleaning and validating for duplicates and other anomalies
• Employing math and statistics into algorithms to generate real-time predictive systems
• Align and adapt business problems to the most efficient machine learning algorithm
• Write code from scratch to create solutions that don’t align with any available turnkey package
• Selecting and explaining the best analytical technique for the problem
• Understanding how to create a computationally efficient solution
• Accurately manage data coming from multiple domestic and internat