Senior Consultant (AVP) - Data Scientist

Role

Skill

Designation

The Senior AI Scientist is a technical role responsible for driving the design, development, and deployment of advanced AI components, models and systems. With 7+ years of experience in artificial intelligence and machine learning, this role is focused on hands-on research, solution prototyping, and enterprise-grade implementation across foundational models, generative AI, and multi-modal applications. The individual is expected to contribute deep technical expertise, execute on complex AI initiatives, and mentor junior scientists. The ideal candidate combines a strong research background with architectural thinking, practical implementation experience, and the ability to collaborate across cross-functional data, business, product and other teams.

Responsibilities

1. Develop the organizations AI research agenda, with a focus on AI (NLP/ML models), foundational models, generative AI, Agentic AI solutions and multi-modal systems aligned to business priorities.
2. Develop end-to-end AI components and capabilities, from ideation and prototyping to scalable, enterprise-grade deployment.
3. Translate cutting-edge research into real-world AI components, perf-ormance optimization, data generation, and integration with existing data and platf-orm ecosystems.
4. Collaborate cross-functionally across product, business and other teams to drive alignment between AI research strategy and enterprise technology roadmaps.
5. Ensure compliance and optimize perf-ormance, covering data governance, industry standards, and model efficiency. Ensure responsible and ethical AI development, incorporating model governance, explainability, fairness, and bias mitigation into the AI lifecycle.
6. The person has to perf-orm testing, validation of the components with reproducible matrix. The person has to perf-orm cross collaboration and work on activities like generation of synthetic data, test suite development, Fine tuning and metrics validation.
7. Good to have - Contribution to Whitepaper, blog authoring / contribution, Github Open source AI projects.

Skills

1. Expertise in software languages like Python / Java / .NET, R, PySpark, etc (Atleast 1 language) and SQL
2. Expertise in developing AI and ML based solutions involving LLMs, NLP, Speech, Video, Agentic AI and other Deep Learning based models. Should have worked on Frameworks and libraries like Tensorflow, PyTorch, ScikitLearn, Ollama, Nemo, Transf-ormers, Torch lightning, NIMS library, Unsloth, etc. Should have exposure working on Fine tuning of LLM models using Open source libraries.
3. Ability to pursue new innovative solutions based on the new and latest technological developments and stacks. Ability to validate the solutions based on metrics, components to be part of larger integral system.
4. Experience in Machine learning models like statistical, time series, stochastic, etc. Possess good concepts in various Machine learning algorithms and metrices.
5. Experience in NLP based solutions like extraction, summarization, cl-assification, etc using libraries like RASA, BERT, etc. Experience in developing chatbots, QA solutions, etc.
6. Experience in replicating the solution for different business streams as per the requirement by fine tuning the models. Experience in using AI Cloud services in developing platf-orm / end to end solutions. Good to have exposure to Cloud based deployment of AI solutions
7. Exposure to atleast 1 Cloud services (AWS, Azure, GCP) is expected
8. Should have experience in developing GenAI solutions making use of cache like RAGs (Chroma DB, FAISS, etc) and internal memory. Good to have experience in developing Hash, GraphAI, etc based NLP components like models, RAGs, etc
9. Capable of communicating AI strategy, technical insights, and roadmaps to senior stakeholders for strategic alignment
10. Solid grasp of data privacy, security, and compliance standards in WNS
11. Adaptability and a continuous learning mindset and excellent communication