Data Science · Gurugram

Key Responsibilities

Project and Practice Leadership

• Own large-scale AI/ML programs, ensuring technical excellence, client satisfaction, and measurable business impact.

• Lead client relationships – drive scoping, solution design, delivery, and executive stakeholder alignment.

• Grow and guide cross-functional teams, setting direction, coaching talent, and ensuring delivery quality.

• Contribute to practice growth through thought leadership, go-to-market development, and capability building.

Generative AI Expertise

• Define GenAI strategy and roadmaps for enterprise clients across NLP, CV, and multimodal use cases.

• Oversee architecture of agentic AI systems, orchestrating multi-step workflows with LangChain, LlamaIndex, AutoGen, and enterprise integrations.

• Establish governance and optimization frameworks for AI agents and RAG pipelines (Pinecone, Weaviate, FAISS, Milvus).

• Advise C-level stakeholders on responsible AI adoption, innovation opportunities, and transformation outcomes.

Cloud Platform Expertise

• Architect and scale cloud-native AI platforms on Azure, AWS, or GCP with focus on compliance, scalability, and cost efficiency.

• Standardize MLOps frameworks for lifecycle management, monitoring, and governance using SageMaker, Azure ML, or Vertex AI.

• Ensure seamless integration of AI solutions with enterprise data ecosystems (data lakes, warehouses, ERP/CRM, real-time pipelines).

• Data Science and Engineering

• Drive high-impact AI/ML solutions (predictive analytics, recommendation engines, optimization models) with measurable ROI.

• Set standards for enterprise data and ML pipelines, enabling scalable and production-ready AI applications.

• Guide innovation and adoption of advanced analytics and multimodal data architectures.

Business Impact and Innovation

• Translate executive business priorities into AI-driven strategies with clear outcomes.

• Shape transformation programs by identifying high-value GenAI/agentic AI opportunities.

• Represent the firm as a thought leader in Data & AI through client advisory, assets, and industry contributions.

Required Qualifications

• Experience: 10+ years in data science, including team leadership and independent client delivery.

• Education: Master’s Degree in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics, or related field).

• Industry Knowledge: Experience in Consumer Tech, Enterprise Tech, or Semiconductors.

Technical Skills

• Programming: Proficiency in Python, SQL, and libraries for NLP and Computer Vision (e.g., Hugging Face, OpenCV).

• GenAI Expertise: Hands-on experience in model development (selection, fine-tuning), model evaluation and optimization, deployment architecture (design, API/integration design), multi-step reasoning workflows, and autonomous agents

• Cloud Platforms: Experience with Azure and/or AWS in data science workflows.

• Data Science Tools: Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

• GenAI & LLM Tooling : LangChain, LlamaIndex, Hugging Face Transformers, vector databases (e.g., FAISS, Pinecone)

• Familiarity with cloud platforms like AWS, Azure, or GCP, especially services like S3, Redshift, BigQuery, or Azure Data Lake.

Preferred Skills

• Experience in decision science projects focused on marketing, supply chain, or sales.

• Strong analytical and problem-solving skills with a results-oriented mindset.

• Excellent communication and stakeholder management capabilities.