Senior Data Scientist – ML & Generative AI

About the Role

Seeking a Senior Data Scientist who is equally comfortable building predictive models and architecting intelligent systems with Generative AI. This role is ideal for someone who thrives on solving complex business problems with the power of data, machine learning, and cutting-edge AI techniques — including large language models (LLMs), RAG pipelines, and prompt engineering.

You’ll be at the forefront of innovation, driving the design and deployment of scalable AI solutions that power intelligent products, enhance automation, and enable smarter decision-making across the organization.

Key Responsibilities

Generative AI & LLMs

• Fine-tune and apply large language models (LLMs) for summarization, classification, generation, and dialogue use cases.
  
• Design and implement retrieval-augmented generation (RAG) pipelines using vector databases.
  
• Develop intelligent agents, agentic workflows and chat-based interfaces that translate natural language into actions or insights.
  
• Build multi-agent orchestration frameworks using tools such as LangGraph, AutoGen, or similar for enterprise-grade use cases.
  
• Create reusable prompt templates and evaluation strategies to ensure output quality and relevance.

Machine Learning & Predictive Analytics

• Develop robust ML models for classification, regression, clustering, and time-series forecasting.
  
• Apply advanced feature engineering, model evaluation, and explainability techniques.
  
• Collaborate with stakeholders to define data-driven solutions aligned with business KPIs.

Deployment & MLOps

• Lead the full model lifecycle from experimentation to deployment preferably using Azure, Databricks, or equivalent platforms.
  
• Monitor model performance, automate retraining, and ensure reliability through MLOps best practices.

Data Strategy & Collaboration

• Work with data engineers to transform raw data into ML-ready datasets.
  
• Collaborate cross-functionally with product managers, developers, and business teams to turn use cases into scalable AI solutions.
  
• Mentor junior team members and contribute to AI/ML best practices across the org.

Required Skills & Qualifications

• 4+ years of experience in data science or machine learning roles.

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  Bachelor's, Master's degree, or Ph.D. in Computer Science, Data Science, Statistics, or a related field.
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  Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning)
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  Hands-on experience with Gen AI-related tech stack, including Azure cognitive search, Langchain, HuggingFace, vector DBs and agent frameworks like Autogen.
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  Experience in fine-tuning open-source models like Llama etc. is a bonus.

• Strong programming skills in advanced python, with experience in SQL and cloud-based data platforms (Azure preferred).
  
• Understanding of model governance, versioning, monitoring, and evaluation.
  
• Ability to translate business problems into analytical frameworks and actionable models.

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  Strong problem-solving mindset and ability to work in ambiguous, fast-paced environments.

• Strong storytelling and stakeholder communication skills.