Join the Thermo Fisher Scientific team to enable customers to make the world healthier, cleaner, and safer through meaningful scientific work
Job Summary
Join the Thermo Fisher Scientific team to enable customers to make the world healthier, cleaner, and safer through meaningful scientific work.
Key responsibilities include designing scalable data pipelines using Python, SQL, and PySpark while deploying machine learning models in AWS environments.
The role requires applying Generative AI techniques such as LLMs and prompt engineering to develop innovative data products and automation solutions.
Matching Summary
Join the Thermo Fisher Scientific team to enable customers to make the world healthier, cleaner, and safer through meaningful scientific work.
Skills & Requirements
Must-have
Python programming skills
PySpark for large-scale data processing
AWS services experience including SageMaker
Machine learning framework expertise
Generative AI and LLM knowledge
SQL and data modeling proficiency
MLOps best practices implementation
Nice-to-have
Cross-functional collaboration abilities
Proactive continuous improvement mindset
Strong analytical problem-solving skills
Ability to explain technical concepts
Knowledge of vector databases and RAG
Key Requirements
3–5 years of experience in data science or applied AI
Strong programming skills in Python and PySpark
Hands-on experience with AWS services like S3 and Lambda
Experience with ML frameworks such as TensorFlow or PyTorch
Exposure to Generative AI technologies and vector databases