Machine Learning Engineer & Senior Data Scientist with a proven track record of delivering
scalable AI systems, GenAI solutions, and enterprise-grade predictive models that directly
improve business growth, marketing ROI, and product performance.
I specialize in end-to-end ML development—from problem framing
and data engineering to deployment and continuous monitoring. My work blends advanced analytics,
software engineering, and business strategy to ensure every model is not only accurate, but
explainable, optimized, and actively used in production. I thrive in high-speed product
environments where AI is more than an experiment—it's a growth engine.
Over the years, I've built solutions across diverse domains: Generative AI & LLMs
with retrieval-augmented generation and AI assistants, Marketing & Product Analytics
including marketing mix modeling and experimentation, MLOps & Deployment
with CI/CD pipelines and API-first architectures, and Predictive Intelligence
for demand forecasting and operational optimization.
My technical achievements include successfully training and integrating Large Language Models
using Azure OpenAI, engineering custom optimization algorithms for marketing analytics, and
delivering solutions for major healthcare and pharmaceutical organizations. I've consistently
driven significant performance improvements, achieving 72% reduction in execution time
and 63% decrease in memory consumption through algorithmic innovation.
As a technical leader, I excel at stakeholder collaboration and translating complex models into
clear business outcomes. I've trained 70+ professionals in machine learning,
Python, SQL, and optimization strategies, building robust data science capabilities across teams.
My approach combines rigorous technical execution with strategic product thinking—ensuring that
every AI solution delivers measurable value and scales effectively in production environments.
