Job Description

Work Schedule

Standard (Mon-Fri)

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.

DESCRIPTION:

Join Thermo Fisher Scientific as an Intern II and be part of our mission to enable customers to make the world healthier, cleaner, and safer. This internship opportunity offers practical experience working with diverse teams across various disciplines. You'll gain valuable exposure to meaningful projects while receiving professional mentorship and development opportunities to support your career growth.

Our interns are matched to projects based on their abilities and current business needs. You'll collaborate with cross-functional teams, contribute to strategic initiatives, and develop practical skills through hands-on experience. Whether you're interested in research and development, engineering, finance, marketing, or operations, you'll have the chance to make significant contributions while building your professional network.

We are looking for a curious and motivated Graduate/Fresher Engineer to join our team and build skills across Data, Automation, and Artificial Intelligence (AI).

This role is ideal for a recent graduate who has strong programming fundamentals, enjoys solving problems, and is interested in learning how data engineering, automation, Generative AI, and cloud technologies are applied to real-world business problems.

You will work alongside experienced team members, contribute to projects, develop prototypes, and gain hands-on experience with modern data and AI technologies.

Responsibilities

As part of the team, you will have opportunities to:

• Work with data using Python and SQL to perform data preparation, analysis, transformation, and basic data quality checks.
• Develop simple scripts, utilities, and automation solutions to improve repetitive or manual processes.
• Learn and contribute to data pipelines and data engineering solutions using technologies such as Python, PySpark, Databricks, and cloud platforms.
• Explore and build Generative AI prototypes using Large Language Models (LLMs), APIs, prompt engineering, and related technologies.
• Experiment with AI-assisted solutions for information extraction, summarization, search, insights, and workflow automation.
• Assist in developing and integrating APIs and software components.
• Create simple reports, dashboards, or visualizations to communicate insights from data.
• Perform testing, validation, debugging, and documentation of solutions.
• Collaborate with team members to understand business problems and translate them into simple technical solutions.
• Learn and follow good software development practices including Git, Agile, CI/CD, data governance, and responsible AI practices.

Skills & Qualifications

We are primarily looking for strong fundamentals, curiosity, and willingness to learn rather than extensive experience with specific technologies.

Essential

• Bachelor’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, or a related field.
• Good programming fundamentals, preferably using Python.
• Basic understanding of SQL, databases, and working with data.
• Understanding of core programming concepts, data structures, debugging, and problem solving.
• Interest in Data Engineering, Automation, AI, and Generative AI.
• Strong analytical and problem-solving mindset.
• Good written and verbal communication skills.
• Ability to learn new technologies and work collaboratively in a team environment.

Good to Have

Exposure through academic projects, internships, certifications, hackathons, or personal projects in one or more of the following areas would be an advantage:

• Python libraries such as pandas or PySpark
• Data platforms such as Databricks
• Cloud platforms such as AWS, Azure, or GCP
• Generative AI and LLMs, including OpenAI APIs, LangChain, LangGraph, or similar frameworks
• Concepts such as prompt engineering, embeddings, RAG, or AI agents
• Automation using Python, APIs, or workflow automation tools
• REST APIs and basic web/service integration
• Visualization tools such as Power BI or Tableau
• Git/GitHub and basic CI/CD or DevOps concepts