Consultant - Dgtl. Trnf.

Company Description

WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees.Design and implement machine learning models, including generative models, to address business challenges.Work with LLMs (e.g., OpenAI, Claude, LLaMA, Mistral) to build intelligent applications and tools.Apply techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).Analyze large datasets to extract insights and support data-driven decision-making.Collaborate with cross-functional teams including product, engineering, and business stakeholders.Develop and maintain data pipelines, model monitoring, and performance evaluation frameworks.Stay current with the latest research and trends in Gen AI and data science.

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.5+ years of experience in data science, machine learning, or AI roles.Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch.Experience with Gen AI tools and frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers).Knowledge on ARIMA,AI/ML, NLP, NLG and Advanced Mathematical foundations of Calculus, Matrices & Data Science is preferredFamiliarity with cloud platforms (Azure, AWS, GCP) and data engineering tools (e.g., SQL, Spark).Excellent problem-solving and communication skills.Experience in utilizing analytical, statistical, and programming skills to collect, analyze, and interpret large data sets.Knowledge of Entity Relationship Diagrams (ERDs) and Extract-Transform-Load (ETL) processesGood to have low-code data platform experiences