Resume
About Me
Data Science Professional with 10+ Years of Expertise in Delivering High-Quality, Data-Driven Solutions
I am a data scientist with over 10 years of experience in machine learning, big data, deep learning, Generative AI, cloud technologies, and agile methodologies. Passionate about solving complex problems, I focus on optimizing processes and delivering impactful, data-driven solutions. With a strong interest in research, programming, and cloud innovation, I’m always eager to explore new technologies and approaches that drive efficiency and scalability.
My Skills
Experience
Sept-2022 to Present
Data Scientist
- Successfully delivered End to end machine learning based project with MLOps implementation where we trained random forest model for Forecasting distribution for CPG based client.
- Optimized the flow with respect to time of execution which resulted in decrease in cost.
- Streamlined HR data analysis by architecting and implementing Azure-based setup and Databricks pipelines, creating an end-to-end automated framework for data-driven decision making. [Demo]
- Utilized Generative AI (GenAI) to tackle complex HR challenges, such as efficiently generating graphs and visualizations for deeper understanding of workforce trends.
- Mentored colleagues on Apache Spark and other relevant tech stacks, empowering them to unlock the potential of data analytics for HR initiatives.
July-2018 to Sept-2022
Data Science Specialist
- Spearheaded the development of a Spark-powered processing engine for e-commerce data, delivering real-time insights to empower marketers. Implemented cutting-edge image and NLP algorithms to extract critical business metrics.
- Developed an ensemble model with Fbprophet and BQML that boosted booking accuracy by 20%. Deep-dived into COVID’s impact on reservations, providing actionable insights for strategic decision-making. Demo
- Pioneered a Django-based voice assistant system that offered seamless control over news, music, and food orders. Leveraged Dialogflow and other APIs to understand user intent and deliver personalized experiences.
- Maximized marketing ROI by 20% with AI-powered revenue prediction model, optimizing channel allocation based on key performance drivers.
- Utilized computer vision to extract hidden insights from ad creatives, uncovering hidden performance drivers and developing a machine learning model that offered actionable recommendations, maximizing ad campaign effectiveness.
Oct-2011 to July-2018
IT Engineer
- Developed and implemented a deep learning-based model using Python and NLTK to categorize user narratives with high accuracy, improving user experience and streamlining operations.
- Leveraged collaborative filtering in Python to recommend triggers for an automotive tool, significantly increasing user efficiency and tool throughput.
- Built a Python-based model that predicts failure time and responsible component using telemetry data, empowering proactive maintenance and cost savings. Additionally, created interactive visualizations with Tableau for clear communication to stakeholders.
- Designed and implemented a MapReduce algorithm in MATLAB to extract and integrate vehicle data from various file formats with DotNet and SQL, achieving a 95% optimization in processing speed. Received Six Sigma Yellow belt certification for the idea.
Education
Masters in Technology in VLSI and Embedded systems
Savitribai Phule Pune University, Pune (July 2016 to June 2018)
- Published papers on Wavelet transform and its implementation
- Voluntered in mentoring in various workshops related to Programming, Xilinx Vivado workshop etc.
Bachelors in Technology in Electronics and Telecommunication
Bharati Vidyapeeth Deemed University, Pune (August 2007 to June 2011)
- Received “Best outgoing student” award from the Department of Electronics, 2011
- Winner of “Newton’s apple” in Bhartiyam, Inter university techfest
- Project related to “Packet transmission and simulation using network Simulator”
Certifications
Publications
Segmentatation based feature extraction of MRI images using Wavelet and implementation on FPGA IEEE
This paper presents a hardware implementation approach for the feature extraction of MRI images using wavelet transform. In this paper wavelet based texture feature extraction method has been proposed.
Texture Feature Extraction Methods and Wavelet Standpoint
Exploring Texture Feature Extraction Techniques for Medical Image Analysis: A Review of Wavelet-Based Methods and Statistical Measures for Enhanced Image Retrieval.
A Review of VLSI Architectures for Discrete Wavelet Transform
Wavelet transform has attracted attention among scientists for signal and image analysis and with its Multiresolution analysis and compression capabilities. This paper surveys different VLSI architectures for implementation of one and two dimensional wavelet transforms.
Honors and Activities
Contact Details
connect@binaychandra.com
+91-727-640-9096
Dwarka, New Delhi, India