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🏢 Philips
Data Scientist (ML/AI)
💼 Fulltime
📍 Bangalore
⏰ Expired
🔗 Explore More
🛠 Skills Required
Python
pandas
scikit-learn
XGBoost
PyTorch
TensorFlow
SQL
AWS
Azure
GCP
PowerBI
Tableau
time-series forecasting
NLP
IoT sensor data analysis
MLOps
Git
Docker
Kubernetes
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🎤 Interview Experience
Philips typically conducts a three‑stage interview process: an online aptitude and coding test, followed by a technical interview focusing on machine‑learning concepts, case studies, and hands‑on coding, and finally an HR round assessing cultural fit and motivation. The difficulty is moderate to high; candidates should be comfortable with end‑to‑end ML pipelines and be ready to discuss real‑world project impact.
🏢 Work Culture
Philips promotes a collaborative, purpose‑driven culture where innovation is encouraged and employees receive ample opportunities for upskilling. The company emphasizes work‑life balance through flexible hybrid arrangements and provides robust health, wellness, and learning benefits.
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📚 Free Study Materials (4)
Aptitude Questions & Answers for Interview Preparation
Covers quantitative, logical reasoning and verbal aptitude topics commonly tested in the first online assessment round.
Open Resource ↗
Philips Recruitment Process Experiences
First‑hand accounts of Philips interview stages, question patterns, and tips to ace the technical and HR rounds.
Open Resource ↗
Philips Interview Guides and Tips
Curated interview preparation material specific to Philips, including sample questions for data‑science roles.
Open Resource ↗
Problem Set for Coding Practice
Extensive collection of coding problems to sharpen algorithmic skills required for the online coding assessment.
Open Resource ↗
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✅ Eligibility Criteria
• Minimum Bachelor’s Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or an equivalent quantitative discipline. • Minimum 4 years of relevant experience in data analytics, data science, machine learning or AI. • Academic performance: 60% or above (or CGPA equivalent). • No active backlogs at the time of joining. • Freshers with strong project work may also be considered if they meet skill requirements. • Candidates graduating in 2025, 2026 or 2027 are preferred, but exact batch year is not mandatory.
🏆 Selection Process
Round 1: Online assessment (aptitude + coding) → Round 2: Technical interview (ML concepts, case studies, coding) → Round 3: HR interview (fit, motivations, compensation).
📋 About the Role
Philips is a global health‑technology leader with a heritage of more than 130 years, headquartered in the Netherlands and operating in over 100 countries. The company focuses on improving people’s health and wellbeing through innovative solutions in precision diagnosis, image‑guided therapy, connected care, and personal health. In India, Philips combines cutting‑edge research with a strong commitment to social responsibility, offering a workplace that values diversity, continuous learning, and a purpose‑driven culture. Employees are encouraged to bring their authentic selves to work, collaborate across functions, and contribute to technologies that directly impact patient outcomes worldwide.
The role of Data Scientist – MR Service Innovation sits within Philips’ Digital & AI team, which is tasked with turning the massive streams of MRI service data into actionable intelligence. As a foundational member, you will help realize the “Autonomous MR” vision by building predictive models, anomaly‑detection algorithms, and self‑healing solutions that keep MRI scanners running with minimal downtime. Your work will directly influence service strategies for thousands of MRI systems across the globe, improving scanner uptime, patient throughput, and overall hospital efficiency.
Key responsibilities include:
1. Design, develop, and deploy machine‑learning models on large‑scale service and IoT sensor data to predict failures and recommend preventive actions.
2. Perform exploratory data analysis on CRM/ITSM datasets (e.g., Salesforce, ServiceNow) to uncover hidden patterns and drive service‑optimization insights.
3. Build time‑series forecasting pipelines for parts demand and maintenance scheduling.
4. Apply natural‑language processing techniques to unstructured technical logs and service tickets.
5. Collaborate with R&D engineers, field service teams, and business leaders to translate analytical findings into actionable business recommendations.
6. Ensure models comply with regulated MedTech standards, maintaining documentation and audit trails.
7. Create interactive dashboards and visualisations for stakeholders using tools such as PowerBI or Tableau.
8. Monitor model performance in production, implement drift detection, and continuously improve algorithms.
9. Contribute to the creation of a data‑driven culture within the MR Service Innovation unit.
10. Mentor junior analysts and share best practices in data science and AI.
Tech stack: Python (pandas, scikit‑learn, XGBoost, PyTorch/TensorFlow), SQL, cloud platforms (AWS/Azure/GCP), Docker/Kubernetes for model deployment, CI/CD pipelines, PowerBI/Tableau for visualisation, and version control (Git). Familiarity with MLOps, REST APIs, and big‑data processing (Spark) is a plus.
Growth path: Starting as a Data Scientist, you will gain deep domain expertise in healthcare AI and regulated environments. The role offers a clear trajectory toward senior data‑science leadership, AI product ownership, or strategic analytics roles within Philips’ broader Digital & AI organisation. Continuous learning opportunities, certifications, and cross‑functional projects accelerate career progression.
Why join Philips? You will work on mission‑critical AI solutions that directly improve patient care, be part of a globally recognised brand with strong R&D investment, and enjoy a hybrid work model that balances office collaboration (minimum 3 days a week) with flexibility. Philips also offers competitive health and wellness benefits, learning stipends, and a culture that celebrates innovation and inclusion.
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📋 Quick Info
JOB ID
C176-J023
POSTED
08 Jun 2026
TYPE
Fulltime
BATCH
All Batches
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