Data Scientist

Overview

Job Description – Data Scientist

We aim to redefine medical image diagnostics by delivering intelligent, holistic, ethical, explainable, and patient-centric solutions. We are seeking innovative problem solvers who can empathize with users, translate business challenges into technical solutions, and design intelligent products. This role is ideal for individuals eager to extend artificial intelligence into unexplored areas, with a strong focus on deep learning applications in medical image analysis.

Responsibilities

• Select, build, and optimize classifier engines using deep learning techniques.
• Analyze problems and apply the most suitable image processing methods.
• Apply deep learning/AI techniques to solve supervised and unsupervised learning tasks.
• Design solutions for complex problems in medical image analysis, including object detection and image segmentation.
• Recommend and implement best practices for statistical modeling.
• Create, train, test, and deploy neural networks for real-world applications.
• Develop and customize algorithms using statistical tools, deep learning frameworks, or bespoke methods to solve business problems.
• Translate requirements into scalable solutions and architectures.
• Participate in sprint planning, code reviews, and other Agile ceremonies to ensure quality deliverables.
• Design and implement scalable ML architectures for training, inference, and deployment pipelines.
• Enforce software engineering best practices within the data science team to ensure code readability, modularity, and maintainability.
• Optimize models for production use (e.g., quantization, pruning, latency reduction for real-time inference).
• Drive adoption of versioning strategies for models, datasets, and experiments (MLFlow, DVC, etc.).
• Contribute to the design of data platforms supporting large-scale experimentation and production workloads.

Skills and Qualifications

• Strong programming and software engineering skills in Python (or other data science languages) with a focus on clean, testable, and modular code.
• Hands-on experience with deep learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs, etc.
• Proficiency in TensorFlow or PyTorch for building, training, testing, and deploying neural networks.
• Proven expertise in computer vision applications.
• Knowledge of data preparation techniques, including augmentation, curation, and synthetic data generation.
• Familiarity with key data science/deep learning libraries: Keras, Pandas, Scikit-learn, NumPy, SciPy, OpenCV, etc.
• Solid foundation in applied statistics: regression, distributions, hypothesis testing, etc.
• Experience working with FastAPI for deploying deep learning architectures.
• Strong analytical and problem-solving skills, with adaptability to emerging technologies.

Good to Have

• Experience building ML architecture components such as feature stores, model registries, and inference servers.
• Solid understanding of software design patterns, microservices, and cloud-native architectures.
• Familiarity with model optimization (ONNX conversion, TensorRT, model distillation).
• Experience working in Agile/Scrum environments with collaborative development practices.
• Exposure to RESTful API development.
• Prior experience in medical image analysis (a strong plus).

Education

• BE/B.Tech in a relevant field (MS/M.Tech is an advantage).

Experience

• Minimum of 2-3 years of professional experience in Data Science/Deep Learning.

Job Type: Full-time

Pay: ₹1,000,000.00 - ₹1,400,000.00 per year

Ability to commute/relocate:

• Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Preferred)

Application Question(s):

• Do you have experience creating software architecture for production environment in AI applications?

Experience:

• FastAPI: 2 years (Preferred)
• PyTorch: 2 years (Required)
• TensorFlow: 2 years (Preferred)
• ONNX: 2 years (Preferred)
• Model Optimisation: 2 years (Required)
• Software Deployment: 2 years (Preferred)

Work Location: In person