Lead Data Scientist | NLP • GenAI • Agentic AI • MLOps
New Delhi, India · Website · he/him

I lead data-science and AI initiatives that move business needles, scale operational systems, and empower people-centric analytics. My focus areas:

• Building production ML/AI systems from data ingestion through deployment and monitoring.
• Applying NLP, GenAI & Agentic-AI to real-world domains (finance, HR, procurement) to surface insights and automate decisions.
• Driving measurable business impact (e.g., 25 % reduction in verification time, improved classification accuracy, faster decision cycles).
• Mentoring teams, collaborating with stakeholders (directors, VPs), and translating strategy into analytics delivery.

• Designed and developed multiple Agentic AI and GenAI solutions to meet rapidly changing business demands across financial, HR, and operational workflows.
• Led end-to-end delivery of production-grade ML systems, from data engineering to model deployment and performance monitoring.
• Built scalable MLOps pipelines with automated retraining, data-drift detection, and real-time model monitoring to ensure long-term reliability.
• Architected NLP-driven automation frameworks that improved information retrieval, reduced processing times, and enhanced decision speed across teams.
• Created analytics and AI accelerators that streamlined workflows, reducing manual effort and increasing process efficiency.
• Collaborated with directors, VPs, and cross-functional stakeholders to shape AI strategy, define success metrics, and ensure measurable business outcomes.
• Mentored data scientists and engineers, establishing best practices for model development, evaluation, and operationalisation.
• Delivered explainable, business-aligned machine learning solutions that improved insights visibility, forecasting accuracy, and operational transparency.

Languages: Python · SQL
ML & AI: TensorFlow · PyTorch · Scikit-Learn · spaCy · LangChain · Doc2Vec
GenAI / Agentic: LLMs · RAG · Agents · Prompt Engineering
MLOps: Airflow · MLflow · Docker · Evidently
Cloud: AWS (SageMaker, Lambda, S3)
Apps & Tools: Streamlit · FastAPI · GitHub Actions

• Agentic AI systems for workflow automation and orchestration.
• Advances in large-language-model fine-tuning for domain-specific use-cases (HR/People Analytics).
• Explainable AI and monitoring frameworks for production systems (bias detection, drift).
• Mentorship frameworks and team scaling in analytics organisations.

• LinkedIn: [https://www.linkedin.com/in/piyushsukhija/]
• Email: [[email protected]]
• Open to: Leadership/Technical roles in Data Science, Generative AI across domains, finance, HR, Pharmaceutical and collaborative research.