Meet Khatri

WORK HISTORY

EDUCATION

SKILLS

ABOUT MEET KHATRI

Data Engineer & Data Scientist with 6+ years of experience designing scalable ML/AI solutions and building robust data pipelines in cloud environments (AWS, Azure). Specialized in time series forecasting, LLM applications, and production-grade ETL systems. Proven ability to lead cross-functional teams, optimize data systems, and deliver analytics products with measurable business impact. Adept at transforming ambiguous business requirements into engineered data products in biotech, manufacturing, and enterprise contexts.AREA OF EXPERTISE• Languages: Python, SQL, R• Libraries: Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, FastAPI, spaCy, LangChain• ML/AI: Supervised/Unsupervised Learning, Deep Learning, NLP, Anomaly Detection, Time Series Forecasting, RAG, LLMs, Prompt Engineering• Data Engineering: AWS (S3, Glue, Lambda, Athena), Azure ML, Spark, Airflow, Kafka• Visualization: Plotly, Dash, Matplotlib, Seaborn, Streamlit, Power BI, Tableau• DevOps: Git, Docker, Kubernetes, CI/CD, Unit Testing• Statistical Methods: Regression, ANOVA, Time Series, SPC, A/B Testing• Soft Skills: Leadership, Communication, Strategy, Stakeholder Management, Team BuildingKEY ACCOMPLISHMENTS• $14.2M Cost Savings: Led integration of advanced analytics into vaccine manufacturing, improving decision-making efficiency by 30%.• Global Project Leadership: Led a high-impact, 3-month international project in France, achieving a 55% reduction in monitored parameters and integrating advanced statistical tools, demonstrating global leadership and technological expertise.• Predictive Uplift: Deployed ML models that improved production yield by 13% and automated root cause analysis for process deviations.• Generative AI Productization: Delivered multiple LLM-based internal tools (chatbots, document automation) with FastAPI, LangChain, and RAG architecture.• Technical Leadership: Directed sprint planning, mentored analysts, and enforced code standards across agile teams delivering real-time data products.• Quality Insights: Applied advanced statistical methods (regression, ANOVA, time series) to identify quality improvement opportunities and process drift.• Real-time Analytics: Orchestrated near real-time data pipelines with Airflow, reducing latency by 60% and enhancing operational responsiveness.