Data Scientist

Job Title

Data Scientist

Job Description

Data Scientist

We're seeking with strong expertise in Agentic AI, Generative AI , Machine Learning, Predictive modelling, time-series analysis, longitudinal pattern mining to join our team. In this role, you will design and build innovative and ethically responsible AI solutions that effectively address real-world problems, balancing technical feasibility with user needs and business impact.

Your role:

• •Design, train, and evaluate LLM-based solutions for various use cases, including retrieval-augmented generation (RAG), information retrieval & search, chatbots,
• •structured information extraction and named entity recognition, text generation, summarization, and more
• •Design, develop, and deploy a Machine Learning, Predictive modelling.
• •Design, develop, and deploy agentic AI systems and autonomous AI workflows using large language models and advanced reasoning architectures
• •Perform the time-series analysis, longitudinal pattern mining on the data sets.
• •Perform the Research & Analysis (Example literature survey)
• •Clean, preprocess, and curate data for evaluation, fine-tuning, and training
• •Work closely with stakeholders across the organization to understand business needs, formulate problems, and deliver data-driven insights
• •Keep up the latest advancements in generative AI research and integrate new techniques into the development process

You are fit if:

• •You hold a master’s or Ph.D. in Computer Science, Data Science, or a related field
• •You have at least five years hands-on experience developing AI/ML systems, with significant experience in LLMs, Generative AI, or AI agents in a professional or enterprise environment
• •You are proficient in Python and relevant libraries for data science and deep learning (e.g., NumPy, Pandas, TensorFlow, PyTorch)
• •You have a strong understanding of classic NLP and LLM-based approaches and hands-on experience with LLM-based architecture, such as RAG, prompt engineering, data synthesis, automatic evaluation, fine-tuning and agent frameworks
• •Hands-on experience building and then iteratively refining model pipelines end-to-end, from data curation to evaluation
• •Familiar with cloud computing platforms
• •Experience with at least one GenAI platform (AWS Bedrock, Co-pilot, OpenAI, etc)
• •Excellent communication skills and a collaborative mindset are essential
• •Strong analytical and problem-solving skills, with attention to detail, round out your profile

Preferred Skills:

• •Data Analysis & Interpretation
• •Prompt Engineering
• •Agentic AI
• •Generative AI
• •Predictive modelling
• •Time-series analysis
• •Longitudinal pattern mining.
• •Data Governance
• •Statistical Methods
• •Statistical Programming Software
• •Business Intelligence Tools
• •Data Mining
• •Machine Learning Engineering Fundamentals
• •Machine Learning & Deep Learning
• •Model Development & Deployment
• •Research & Analysis
• •Requirements Analysis
• •Root Cause Analysis (RCA)
• •Data Quality Management Systems
• •Regulatory Compliance

• How we work together:
• We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

Onsite roles require full-time presence in the company’s facilities.

Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.

This role is an office-based role.

• About Philips:
• We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
• •Learn more about our business .
• •Discover our rich and exciting history .
• •Learn more about our purpose .
• If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here .

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