This role is for one of the Weekday's clients Min Experience: 10 years Location: Gurugram JobType: full-time We are seeking an experienced Senior Data Science & GenAI Specialist with 10–16 years of industry experience to drive advanced analytics, machine learning, and generative AI initiatives across business functions.
The ideal candidate should have strong expertise in Data Science with Python and hands-on experience building scalable AI/ML solutions, with a growing focus on Generative AI (GenAI) applications.
This role involves working closely with business leaders, engineering teams, and stakeholders to design, develop, and deploy intelligent solutions that solve complex business problems and create measurable impact.
Key Responsibilities: Design, develop, and deploy end-to-end data science and AI solutions using Python and modern machine learning frameworks.
Build predictive, prescriptive, and classification models for solving business challenges across multiple domains.
Develop and implement Generative AI use cases including content generation, summarization, conversational AI, recommendation systems, and workflow automation.
Work with structured and unstructured datasets, performing data cleaning, feature engineering, model training, validation, and optimization.
Collaborate with cross-functional teams to identify business opportunities where AI/ML and GenAI can create operational efficiency or product innovation.
Develop scalable machine learning pipelines and integrate models into production environments.
Fine-tune and optimize foundation models or integrate APIs for GenAI solutions.
Conduct model performance monitoring, A/B testing, and continuous improvement of deployed solutions.
Mentor junior data scientists, ML engineers, and analysts on best practices in data science and AI development.
Stay updated with emerging trends in AI, machine learning, and generative AI ecosystems.
Translate business requirements into technical AI/ML roadmaps and architecture recommendations.
Ensure governance, model explainability, and responsible AI practices are followed.
Required Skills (Must Have): 10–16 years of hands-on experience in Data Science and advanced analytics.
Strong expertise in Python for data science, machine learning, statistical analysis, and automation.
Proven experience with libraries/frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar.
Hands-on experience in Generative AI (GenAI) including prompt engineering, model orchestration, retrieval-based systems, or AI application development.
Strong understanding of machine learning algorithms, statistics, predictive modeling, NLP, and deep learning.
Experience in model deployment, MLOps, and scalable AI solution implementation.
Strong problem-solving, analytical thinking, and stakeholder communication skills.
Good to Have Skills: Experience working with Large Language Models (LLMs) such as GPT, open-source LLMs, or enterprise AI platforms.
Exposure to broader AI/ML ecosystems including computer vision, NLP, reinforcement learning, or neural networks.
Familiarity with cloud platforms such as AWS, Azure, or GCP for AI workloads.
Experience with vector databases, embeddings, LangChain/LlamaIndex, or RAG pipelines.
Knowledge of CI/CD pipelines and model lifecycle management.
Preferred Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related field.
Advanced certifications in AI/ML, Data Science, or Generative AI are a plus.
Prior experience leading enterprise-scale AI transformation initiatives is preferred.
