SAPNA SINHA
Learn its ways, watch it, be careful of hasty guesses at its meaning. In the end you will find clues to it all.” - H.G. Wells
Learn its ways, watch it, be careful of hasty guesses at its meaning. In the end you will find clues to it all.” - H.G. Wells
Hi there! 👋 I'm Sapna, a data adventurer, pattern whisperer, and problem-solver with 10+ years of experience turning messy data into meaningful magic!🚀 I've worked across e-commerce, insurance, and automotive domains, crafting real-time data products and predictive models that don't just look smart - they actually do smart things. From customer analytics to machine learning, NLP to deep learning, my toolbox is full, my curiosity is endless, and my goal is always the same: to turn data into delightfully useful decisions.
I'm on the lookout for my next big challenge - a space where I can blend logic with creativity, structure with spontaneity, and technology with true impact. I want to build with purpose, lead with empathy and collaborate with humans who love innovation as much as I do💯.
If you've got a role where data storytelling meets machine intelligence (and maybe a bit of joy on the side), let's talk! I bring the skills, the spark, and a love for learning that just won't quit.
By looking at past roadside assistance requests and real-time service data, service providers can find ways to do a better job. This information can help them get to breakdowns faster, handle more service calls, and keep customers happier overall.
By combining customer trends with data from customer interactions, organisations can better understand and predict customer behaviour. This helps them plan their services more effectively to meet customer needs.
Biomarkers in certain diseases can help detect health issues early, encouraging people to take action sooner. This not only benefits the individual but also helps reduce the strain on the healthcare system.
Advanced text analytics techniques are used to analyse logs, making it easier to identify, understand, and debug software test failures in car infotainment systems.
Industrial data with labelled intrusions is used to compare different machine learning models and identify which one is most effective for detecting security threats.
My ongoing research focuses on privacy-preserving AI models and the implementation of responsible AI practices across organisations, with the goal of identifying effective strategies and lessons that can guide future development and policy.