Data Scientist

Cyient; Bengaluru; On-site; INR 2,600,000 - 4,800,000; Full time

Job summary

Philips is seeking an experienced AI/ML professional to collaborate on applied AI use cases in clinical imaging and supply chain. You will contribute to model development, validation, and deployment while working with cross-functional clinical, engineering, business, and IT stakeholders.

You will support data preparation, model training and evaluation, and ensure quality and explainability of AI solutions across enterprise environments.

Qualifications

• 3–5 years of AI/ML, data science, or applied AI engineering.
• Strong Python, ML and data analysis skills.
• Experience with DL, transformers, and modern AI frameworks.
• Experience in medical imaging or healthcare AI, or supply chain analytics.

Responsibilities

• Collaborate with Philips teams on applied AI use cases across clinical imaging and supply chain.
• Develop, evaluate, and refine AI/ML models including CV, generative AI, predictive modelling.
• Translate problem statements into AI requirements with stakeholders.
• Support data preparation: cleansing, validation, annotation review, dataset readiness.
• Develop, train, retrain, and fine-tune AI models and assess performance and explainability.
• Integrate AI models into deployable workflows with software, platform, and DevOps teams.
• Contribute to model lifecycle: tracking, versioning, monitoring, and documentation.
• Participate in design reviews, testing, and knowledge-sharing with Philips team.

Skills

AI/ML

Python

Generative AI

Computer Vision

Deep Learning

PyTorch

TensorFlow

Data Analysis

MLOps

Tools

PyTorch

TensorFlow

Experiment Tracking

Model Deployment

Monitoring

Job description

• Minimum 3-5 years of experience in AI/ML, Data Science, or Applied AI Engineering.
• Strong proficiency in Python, machine learning, and data analysis.
• Hands-on experience with deep learning, transformer-based architectures, and modern AI frameworks (e.g., PyTorch, TensorFlow).
• Experience in one or more of the following domains: computer vision, generative AI, foundation models, diffusion models, predictive modelling.
• Developing, validating, and deploying AI/ML solutions in production or enterprise environments.
• Working with cross-functional teams comprising of domain experts, software engineers, product owners, and business stakeholders.
• Experience in medical imaging, healthcare AI, supply chain analytics, or other applied AI domains.

Required Skills:

• Generative AI

2. Clinical Imaging AI

• Medical imaging AI
• Image quality assessment

3. Data Quality & Validation

• Data cleansing
• Annotation review
• Dataset readiness
• Statistical validation
• Failure analysis

4. Deployment & MLOps

• Experiment tracking
• Deployment support
• Monitoring
• Documentation
• Cross-functional collaboration
• Requirement clarification
• Technical documentation - compliant with defined procedures and templates

Job Responsibilities:

• Collaborate with Philips teams on applied AI use cases across clinical imaging and supply chain domains.
• Contribute to the development, evaluation, and refinement of AI/ML models, including computer vision, generative AI, predictive modelling, and optimisation-based approaches, depending on the use case.
• Work with clinical, engineering, business, and IT stakeholders to translate problem statements into clear AI requirements, success criteria, data needs, and measurable outcomes.
• Support data preparation activities such as data cleansing, validation, quality checks, annotation review, dataset structuring, and readiness assessment to ensure reliable model development and evaluation.
• Develop, train, retrain, and fine-tune AI models using appropriate techniques, including statistical analysis, hypothesis testing, performance evaluation, explainability, and failure analysis.
• For clinical imaging use cases, contribute to image-based AI model development and validation, including MRI image generation, artefact detection, image quality assessment, and model explainability.
• For supply chain use cases, contribute to AI solutions involving forecasting, decision intelligence, workflow automation, and data-driven process improvement.
• Integrate AI models into deployable workflows or product environments in collaboration with software, platform, and DevOps teams, ensuring performance, scalability, reliability, and maintainability.
• Contribute to model lifecycle activities, including experiment tracking, model versioning, monitoring, documentation, validation evidence, and continuous improvement.

Participate actively in design discussions, code reviews, testing, quality assurance, and knowledge-sharing activities, while working closely with Philips team members in a collaborative delivery model.