Khushboo Patel

About Khushboo Patel

Hi, I’m Khushboo I build products powered by AI, data, and curiosity — turning complex problems into simple, impactful solutions. A few highlights from my journey so far: Built SubScape™, an AI-powered predictive toolkit that helps streaming platforms reduce churn & optimize ROI.🤖 Trained neural networks to detect stress, age, and gender using physiological data + computer vision. Designed dashboards & simulations that guided multimillion-dollar business decisions for clients. Use AI daily — from coding & debugging to automating workflows, creating content, planning workouts, and even learning piano.I’m not just a data scientist — I’m a full-stack builder:‍ I code (Python, SQL, R) I design and prototype (Streamlit, BI tools, Figma, GPT-4, Gemini, Loveable)🧠 I think like a product person (customer-focused, fast iterations, business-first mindset) My superpower? A growth mindset. I learn fast, ask smart questions, and love experimenting until things click.If you’re excited about AI-native products, creative problem-solving, or data-driven innovation, let’s connect!

Experience

1. Senior Data Scientist

   Magid

   Nov 2022 — Present · New York, NY, US

   Developed SubScape™, a predictive analytics toolkit that helps streaming services manage churn and retention, optimize subscriber acquisition and retention, and guide investment decisions using AI-driven simulations- Enabled clients to gain competitive insights and forecast ROI through a comprehensive dashboard, supporting strategic business decisions in the highly competitive SVOD landscape- Conducted comprehensive research, designed and implemented surveys, performed advanced data analysis and modeling, and developed algorithms and models to enhance key business metrics- Successfully addressed business questions related to customer engagement, conversion, retention, and churn, leading to improved operational efficiency and strategic decision-making- Analyze complex and unstructured data sets to generate insights and recommendations for business improvement, leveraging statistical modeling and machine learning techniques using Python, R and SQL. Successfully address business questions related to customer engagement, conversion, retention, and churn, leading to improved operational efficiency and strategic decision-making- Utilize advanced statistical techniques and clustering algorithms to segment customers and optimize marketing strategies, resulting in improved engagement and conversion rates to extract actionable insights- Design and implement automated ETL pipeline for handling survey data ensuring efficient data extraction, transformation and loading processes while employing indexing and partitioning strategies to enhance query performance- Design and develop interactive Dundas BI dashboards, providing clients with real-time insights into industry trends by integrating real-time data feeds for customized metric tracking and historical analysis- Conducted sentiment analysis on survey data to extract actionable insights for enhancing viewer engagement and informing content and marketing decisions in Python.

Education

• Nirma University

  Bachelor of Technology - BTech

  2015 — 2019

• University of the Pacific

  Master of Science - MS, Data science

  2019 — 2021