About company:

Thermo Fisher Scientific Inc. is the world leader in serving science, with an annual revenue of approximately $40 billion. Our mission is to enable our customers to make the world healthier, cleaner, and safer. Whether our customers are accelerating life sciences research, solving sophisticated analytical challenges, delivering efficiency in their laboratories, or improving patient health through diagnostics—the design, development, and manufacturing of life-changing therapies—we are here to support them. Our global teams of more than 100,000 colleagues deliver an outstanding combination of innovative technologies, purchasing convenience, and pharmaceutical services through our industry-leading brands, including Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon, and PPD. For more information, please visit www.thermofisher.com

About team:

Providing outstanding product development services to Thermo Fisher Scientific global business units is one of the essential functions of the India Engineering Center (IEC). This global research and development center, established in 2009, is located in HiTech City, Hyderabad, with over 150 employees. We are a team committed to developing innovative and groundbreaking technologically sophisticated products ranging from laboratory equipment, analytical instruments, remote monitoring solutions, chromatography, and mass spectrometry. We are proud of the work that we do at IEC, thereby fulfilling our mission of making the world a healthier, cleaner, and safer place.

About the job:

The ideal candidate will be developing and implementing AI and machine learning solutions to solve real-world problems. Candidate would also be working hands on working on big process data and assisting team in making sense of data interpretation and visualization.

Role Purpose Summary:

• Proficient in either Python programming or dplyr (R).experience with data wrangling and preprocessing using libraries such as pandas (Python) or dplyr (R).
• Understanding of machine learning, large language models, Data interpretation & handling is important. Knowledge on computer vision, natural language processing, would be added advantage
• Working knowledge of fundamental statistical concepts and methods.
• Designs, constructs, and optimizes prompts in a way that optimally guides the AI model's generation process to provide targeted and contextually correct responses.
• Responsible for designing and implementing systems that apply profound machine learning techniques, which enable the creation of new, original content. This role also includes applying the technology in various applications, managing the system's performance, and handling the ethical considerations associated with its use.
• Experience with popular AI/ML frameworks and libraries
• Solid understanding of fundamental concepts in machine learning and artificial intelligence.
• Familiarity with popular machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Ability to work independently as well as collaboratively in a team environment.
• Excellent problem-solving skills and attention to detail.
• Strong communication and interpersonal skills.

Job Title: Data Analyst I

Roles & responsibilities:

• Research, develop, and implement appropriate statistical models & visualization of data for managment reviews
• Analyze and implement strategies for data collection, extraction, and pre-processing.
• Carrying out the preprocessing of structured and unstructured data while assisting in collecting, cleaning, and preprocessing data for analysis.
• Processing, cleansing, and validating the integrity of data to be used for analysis.
• Perform rigorous testing and validation of AI/ML models to ensure accuracy, reliability, and robustness.
• Assist in optimizing and fine-tuning AI and ML models to improve performance and efficiency.
• Document and communicate the technical details, progress, and analysis insights to team members and key customers
• Support the development and implementation of ML models and algorithms.
• Conduct experiments and tests to evaluate the model's performance and identify areas for improvement.
• Work on tasks related to data visualization, feature engineering, and model interpretation.
• Document and present findings, insights, and results to the team.
• Stay updated on the latest advancements and best practices in AI/ML research and technology.