Principal Data Scientist

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

**About Lilly**:
At Lilly, we unite caring with discovery to make life better for people worldwide. We are one of the Top 10 most valued companies of the world, and global **healthcare leader** headquartered in Indianapolis, Indiana. Our 44,000 employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the globe.
- We have pioneered the development of several significant drugs and treatments over the years - and strong pipeline including being the _first to mass produce insulin, penicillin, tuberculosis (MDR-TB) and polio vaccines_**_._**_ _

At Lilly, our research and _product-oriented mindset _and focus on _Accelerate, Reach and Scale using new-gen technologies _helps us redefine what is possible through technology in pharma. _Impact driven growth _combined with a commitment to make a _real difference in lives _makes Lilly _the place of choice _for the_ best talent _to come together and be at the _forefront of innovation and acceleration_.

Join us _to make significant difference in the well-being of people worldwide._

**Job Title**:Data Science
**Job Level**: Principal Scientist I/II - Data - Advanced Analytics - LCCI

**Experience Level**: 7 to 10 Years
**Qualification and Eligibility criteria**: B.Tech./Masters/PhD. in Computer Vision related field
**Location**: India - Bengaluru

**Purpose of the Role**:
The Data Scientist collaborates directly with business stakeholders to design and deploy state-of-the-art machine learning, deep learning, optimisation, and computer vision algorithms. These solutions address complex challenges across diverse domains, including manufacturing vision-based inspections, medical imaging, robotics vision, and finance. This role requires a proactive approach to developing and deploying algorithms in suitable environments to achieve impactful results.

**Key Responsibilities**:
2. Handle imbalanced, noisy, and high-dimensional datasets, ensuring robust and scalable outcomes.

3. Partner with cross-functional teams to solve problems in manufacturing, medical imaging, robotics vision, finance, etc.

4. Configure and integrate imaging systems, including cameras and sensors, for diverse operational settings such as labs, manufacturing floors, and robotics systems.

5. Build and optimize models for various scenarios, including real-time inference, batch processing, and edge computing.

6. Lead the end-to-end lifecycle of model development, deployment, and performance monitoring across different environments, including labs, manufacturing floors, and edge devices.

7. Leverage machine learning, optimisation, and deep learning techniques to enhance manufacturing line capacity and reduce downtime.

8. Utilize CI/CD workflows, version control systems (e.g., Git), and Docker to ensure reproducible and efficient research processes.

9. Leverage expertise in image annotation tools and image registration methods for domain-specific challenges.

10. Mentor team members and foster collaboration within cross-functional teams to drive innovation and solve technical problems

**Essential Tech knowledge**:
**Core Software Development and Programming**

1. Advanced proficiency in Python; experience with C++ is a plus. Familiarity with scalable software development practices and integration of hardware systems into software solutions.

**Core Computer Vision Expertise**

2. Proficiency in traditional algorithms (e.g., edge detection, feature extraction) and modern deep learning approaches (e.g., CNNs, object detection, and segmentation).

3. Experience with image processing libraries such as OpenCV, PIL, and scikit-image.

4. Knowledge of 3D point cloud processing, essential for LiDAR and object reconstruction tasks.

**Deep Learning and Machine Learning**

5. Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, and Keras.

6. Expertise in vision-based architectures like LeNet, ResNet, YOLO, UNet, EfficientNet, and SAM.

7. Familiarity with optimisation techniques, including model quantisation, pruning, and deploying real-time inference on edge devices.

**Data Acquisition and Image Handling**

8. Knowledge of various imaging modalities (R