Group Manager - Data Science and Generative AI

Group Manager- Data Science + Gen AI

Company Description

WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.

Job Description

Data Scientist + Gen AI

Location : Gurugram

Exp - 8 - 10 Years

Immediate joiners are preferred

Role

We are looking for a senior data scientist with a proven ability to translate complex business challenges into impactful, data-driven solutions. The ideal candidate combines strategic thinking with deep technical expertise in AI and machine learning, strong communication skills, and effective stakeholder and client management.

The candidate should be highly proficient in Generative AI, Agentic AI, Python programming and end-to-end project delivery, with a track record of building high-performance GenAI/ML solutions that streamline and enhance analytical process.

Job Description

Understand customer business challenges and define appropriate analytics approaches to design effective data-driven solutions.Communicate complex technical concepts clearly and effectively to both technical and non-technical audiences, including senior business stakeholders.

Leverage the latest Generative AI tools to design and develop innovative applications that address real-world problems.Apply advanced data science techniques including data preprocessing, feature engineering, and model development.Leverage GenAI models (e.g., GPT, DALL·E, LLaMA) for content generation, data exploration, and intelligent automationSound knowledge of GenAI frameworks (e.g., OpenAI, Hugging Face, Meta AI, LangChain, LangGraph)Deploy scalable AI solutions using cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

Integrate CI/CD pipelines for model training, testing, and deployment.Monitor model performance, ensure reliability, and manage lifecycle of deployed agents.Experience processing large volume of data and build data science models using Python demonstrating strong analytical and problem-solving skills.

Apply Machine Learning techniques hands-on in various business scenarios, including end-to-end model development and deployment.Utilize Natural Language Processing (NLP) techniques to extract insights from unstructured data sources.Confidently present and socialize business recommendations, enabling customers to act upon and implement these solutions effectively.Required Skills and Experience:

Proven experience in developing machine-learning models from concept to deployment.Strong programming skills in Python and experience with data science libraries and frameworks like Pandas, Numpy, Seaborn, Matplotlib, Scikit-learn, Tensorflow, Keras, OpenCV, NLTK, Spacy, Gensim, TextBlob, Fasttext, FastApiHands-on expertise in developing GenAI and Agentic AI solutions for solving business problems.

GenAI frameworks (e.g., OpenAI, Hugging Face, Meta AI, LangChain, LangGraph)Version Control & DevOps Tools: GitHub (CI/CD Actions), Azure DevOpsVersion control systems (ADO/Bitbucket)Strong understanding of Natural Language Processing (NLP) and unstructured data analytics.Knowledge of any of the visualization tools like PowerBI, Tableau, R Shiny etc. is a plusFamiliarity with web-based application frameworks like Django, Streamlit etc.Ability to work effectively in a collaborative environment with onshore and offshore teams

Functional/Domain Experience:

Good exposure to BFSI domain ( P&C Insurance is preferred)8-10 years of hands on experience in delivering Data Science/GenAI projects.Educational Qualification:BTech/Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1-2 institutions Or BE/B-Tech, MCA or MBA

Qualifications

BTech/Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1-2 institutions Or BE/B-Tech, MCA or MBA

Experience Level

Mid Level