When you’re part of the team at Thermo Fisher Scientific, you’ll do important work. Surrounded by collaborative colleagues, you’ll have the support and opportunities that only a global leader can give you. Our respected, growing organization has an exceptional strategy for the near term and beyond. Take your place on our strong team, and help us make significant contributions to the world.
Location/Division Specific Information
Thermo Fisher Scientific's mission is to help make the world a healthier, cleaner and safer place. As part of our Austin, TX team, this position offers a unique opportunity at Thermo Fisher Scientific to help our mission by leading and executing an enterprise data strategy.
How will you make an impact?
We are looking for an ambitious, talented, and self-motivated individual, who will serve as a technical leader for our data science team focused on applying data science principles to complex problems in the life sciences domain, bringing key insights to our customers. In this role, you will be responsible for defining and executing an enterprise data strategy and architecture that supports the organization’s business strategy.
Working closely with stakeholders, you will develop knowledge models describing relationships between entities using Resource Description Framework concepts. You will develop semantic representations of the domain to improve knowledge sharing across applications and enable automated reasoning.
The role requires working collaboratively across the Technology, Product and Commercial organizations to ensure alignment towards business goals. In this role, you will build strong relationships with cross-functional team members and business stakeholders.
What you will do?
- Lead specification, design, and implementation of advanced analytics projects
- Analyze business workflows and develop new semantic representations of the domain
- Share business and technical learning with the broader engineering and product organization, while adapting approach for different audiences
- Confidently and professionally present and defend recommended solutions, approaches, timelines
- Identify opportunities for different techniques and evaluate which are best
- Design and document APIs leveraging a standard API documentation framework (e.g. Apiary, Swagger)
- Be an evangelist for data science within the company, and help non-technical partners understand how they can benefit from data science
- Act as subject matter expert for advanced analytics, specifically within the domain of NLP
- Stay abreast and evaluate the latest in analytics technologies and determine how to incorporate these into our data science best practices
- Identify opportunities for different NLP techniques and evaluate which are best
- Understand and follow conventions and best practices for analysis, statistics, modeling, coding, and architecture; hold other members of the team accountable for doing so
- Develop and adhere to rigorous testing of statistics, models and code
- Develop training materials and educate others on best practices
- Build strong relationships with cross-functional team members and business stakeholders
- Work collaboratively across the Technology, UX, and Product organizations to ensure alignment towards business goals
- B.S. or M.S. in Computer Science or related field
- Demonstrated experience with semantic web architecture using OWL, RDF, Ontology Repositories, SPARQL and Semantic Services
- Experience developing RESTful APIs
- Working knowledge and experience with Amazon API gateway or other API hosting service
- Hands-on experience designing and documenting internal and external (commercial) APIs leveraging an API documentation framework (e.g. Apiary, Swagger)
- Experience with large-scale consumer-facing production software and cloud deployment strategies
- Agile/Scrum methodology experience
- Strong experience with Linux/Unix/Shell environments
- Proficiency with at least one programming language (such as Java, Scala, .NET, C/C++)
- Experience collaborating with cross functional teams
- Experience with big data and analysis technologies, such as Apache Hadoop, Apache Spark, H2O, preferred
- AWS experience preferred
- Life Science experience preferred, but not required
- Demonstrated understanding of ontology design and authoring
- Proficiency with data analysis languages and tools such as Python/Jupyter or R
- Excellent written and verbal communication skills
- Knowledge of Resource Description Framework concepts and the semantic web, and experience applying those concepts
- Deep understanding of API design, including versioning, isolation and micro-services
At Thermo Fisher Scientific, each one of our 65,000 extraordinary minds has a unique story to tell. Join us and contribute to our singular mission—enabling our customers to make the world healthier, cleaner and safer.