Principal Engineer, Data Science

Nagarro

Principal Engineer, Data Science at Nagarro. Responsible for developing data solutions and collaborating with cross-functional teams to deliver best results.

Posted 6/27/2026full-timeRemote • 🇮🇳 IndiaLeadWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformNumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

Understanding the client’s 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 client’s 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.

Requirements

What you’ll need

Total experience 11+ years
Hands on working experience in data science with a focus on predictive modelling (eg. Statistical Analysis, ANOVA, Time series Analysis, Regression Analysis) and optimization
Strong working experience with Data Science on GCP, Generative AI fundamentals
Strong experience with Python (and/or R) and libraries such as Pandas, NumPy, Scikit-learn
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, Lang Chain, Llama Index, and prompt engineering
Strong understanding of MLOps principles and tools for CI/CD, monitoring, and model lifecycle management
Excellent communication skills and the ability to collaborate effectively with cross-functional teams.

Benefits

Comp & perks

Employees can work remotely

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencepredictive modellingstatistical analysisANOVAtime series analysisregression analysismachine learningmathematical optimizationnatural language processingMLOps

Soft Skills

communicationcollaborationproblem-solvinganalytical thinkingtechnical designdecision-makingguideline definitionreviewing architecturesystematic analysisclient requirements understanding