Staff Engineer (Data science) at Nagarro

, , India -

Full Time

Start Date

Immediate

Expiry Date

08 Feb, 26

Salary

0.0

Posted On

10 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, Data Preprocessing, Model Evaluation, NLP, MLOps, Cloud Platforms, RESTful APIs, Docker, Kubernetes, Explainable AI, Conversational AI

Industry

IT Services and IT Consulting

Description

Company Description 👋🏼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 scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Job Description REQUIREMENTS: Experience : 6+ Years Role focuses on designing, developing, and deploying machine learning models to support AI-driven banking solutions. Seeks 7-10 years of experience in AI/ML engineering, ideally within banking or financial services. Expertise in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face for model development. Strong understanding of supervised and unsupervised learning algorithms, feature engineering, and data preprocessing. Experience with model evaluation techniques and performance metrics (accuracy, precision, recall, F1-score). Familiarity with AI use cases in banking, including fraud detection, personalization, credit scoring, and churn prediction. Proficiency in cloud-based ML platforms like Azure ML, AWS SageMaker, and Google Vertex AI for model deployment. Knowledge of MLOps frameworks for CI/CD, model lifecycle management, and monitoring (MLflow, Kubeflow). Ability to build explainable AI models using SHAP, LIME, and ensure compliance with regulatory standards. Hands-on experience with NLP and LLM engineering, including fine-tuning, prompt engineering, and RAG architectures. Familiarity with vector databases (FAISS, Pinecone), orchestration tools (LangChain, LlamaIndex), and conversational AI frameworks. Strong backend integration skills using RESTful APIs, containerization (Docker, Kubernetes), and microservices architecture. Professional certifications such as TensorFlow Developer, AWS ML Specialty, or Google Professional ML Engineer are preferred. RESPONSIBILITIES: Understanding functional requirements thoroughly and analysing the client’s needs in the context of the project Envisioning the overall solution for defined functional and non-functional requirements, and being able to define technologies, patterns and frameworks to realize it Determining and implementing design methodologies and tool sets Enabling application development by coordinating requirements, schedules, and activities. Being able to lead/support UAT and production roll outs Creating, understanding and validating WBS and estimated effort for given module/task, and being able to justify it Addressing issues promptly, responding positively to setbacks and challenges with a mindset of continuous improvement Giving constructive feedback to the team members and setting clear expectations. Helping the team in troubleshooting and resolving of complex bugs Carrying out POCs to make sure that suggested design/technologies meet the requirements. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

Responsibilities

The role involves understanding functional requirements and analyzing client needs to define overall solutions. It also includes leading application development and addressing issues while providing constructive feedback to team members.