Navyanka T.
Lead Data Scientist (Client Microsoft) @LTIMindtree
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WORK HISTORY
Lead Data Scientist (Client Microsoft) @LTIMindtree
Toronto, ON, CA
Drove cross-functional analytics for Bing Places using Machine Learning, Azure Synapse, and LLM-based Generative AI for anomaly detection & root cause analysis — improved KPI trends by ~15% via proactive insights.Automated causal analysis pipeline with Explainable AI (SHAP), reducing manual analysis time by 40% and accelerating data-driven decision-making.Pioneered prompt engineering techniques for LLMs to generate plain-language business summaries of SHAP outputs & KPI trends, enhancing stakeholder adoption and actionability.Built & maintained interactive Power BI and Titan dashboards for real-time KPI monitoring, empowering 10+ managers to respond faster to market and operational changes.Partnered with product, engineering, and compliance to deploy ML solutions aligned with strategic goals & regulatory standards, ensuring smooth integration into business workflows.
EDUCATION
Miracle Educational Society Group of Institutions
Bachelor of Technology - BTech, Computer Science
Dalhousie University
Master's degree, Data Science
ABOUT NAVYANKA T.
Senior Data Scientist with a Master’s degree in Data Science and 6+ years of experience designing and deploying end-to-end AI/ML solutions in production for enterprise clients. Expertise spans Large Language Models (LLMs: GPT‑3.5, GPT‑4), Generative AI applications, advanced NLP (BERT, topic modeling), predictive modeling, and unsupervised learning (clustering, anomaly detection). Proven track record in architecting scalable ML pipelines on Azure Databricks and integrating with Azure Synapse, MLflow, and Power BI for real-time analytics and decision-making. Skilled in prompt engineering, Explainable AI (SHAP, LIME), and building automation workflows that cut operational overhead by up to 80%. Strong focus on ML Ops best practices — CI/CD for ML, automated retraining, model monitoring, and compliance alignment — ensuring high-availability, low-latency, and business-aligned AI systems.
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