Principal Engineer, Data Science

We're Nagarro.

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!

REQUIREMENTS:

• Total experience 13+years.
• Hands on working experience in data science with a focus on predictive modeling and optimization.
• Strong experience with Python (and/or R) and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch.
• Strong knowledge of Cloud Architecture and deployment of data solutions in cloud ecosystems (e.g., AWS, Azure, GCP).
• Proven expertise in machine learning, mathematical optimization (e.g., LP, IP, genetic algorithms, RL), and NLP techniques.
• Familiarity with Generative AI fundamentals and hands-on experience with RAG, LangChain, LlamaIndex, and prompt engineering.
• Strong understanding of MLOps principles and tools for CI/CD, monitoring, and model lifecycle management.
• Experience in Reinforcement Learning, Ant Colony Optimization, or other advanced AI methodologies.
• Familiarity with containerization tools (e.g., Docker, Kubernetes) for model deployment.
• Hands-on experience with version control, MLflow, or similar experiment tracking tools.
• Strong interpersonal and communication skills to interact with business and technical teams effectively.

RESPONSIBILITIES:

• Writing and reviewing great quality code
• Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the clients requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it.
• Understanding and relating technology integration scenarios and applying these learnings in projects
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.