Mr. Shreyas Mahimkar

Shreyas Mahimkar is a skilled Data Scientist at LiveRamp, with extensive experience in the consumer electronics industry. He excels in Python, Java, Apache Spark, and database management, holding a Master's Degree in Computer Science from Northeastern University. Shreyas has previously worked at Data Plus Math and TiVo, where he developed data pipelines, predictive models, and clustering methods to enhance TV viewership insights. His projects include predicting crime locations using big data and developing a web crawler. He has also interned at Novartis, contributing to big data analysis with Spark. Shreyas's background combines strong technical skills with practical experience in data science. Shreyas Mahimkar is a seasoned Senior Data Scientist and Engineer at LiveRamp with over five years of experience in leveraging data to drive business solutions and innovation. His expertise lies in transforming complex data into actionable insights, leading multiple Proof-of-Concept projects, and building innovative data products that enhance campaign reporting and marketing efficiency. Proficient in Python, Java, SQL, and Apache Spark, Shreyas has contributed significantly to revenue growth through technical leadership and collaboration on cutting-edge data science projects. At LiveRamp, Shreyas has been instrumental in designing and deploying advanced data science solutions. His contributions include developing a Market Mix Modeling (MMM) framework that utilizes Bayesian combiners to integrate national and regional ad performance data, improving marketing spend attribution accuracy by 40%. This innovative approach helped secure a $1 million revenue deal by demonstrating incremental ROI to enterprise clients. He also operationalized the first Reach Frequency Model using SparkSQL for large-scale digital activation, leading to a multi-million-dollar client contract. Shreyas’s efforts in building a linear attribution system integrating causal impact analysis and multi-touch attribution modeling led to rapid adoption by 10+ enterprise clients in the first quarter of deployment. Apart from product development, Shreyas has excelled in creating standardized experimental analysis pipelines, winning company hackathons for innovative batch campaign reporting systems based on Intent-to-Treat (ITT) and Per Protocol (PP) causal frameworks. His optimizations in SparkSQL reduced client implementation processing time by 60%, showcasing his ability to enhance efficiency across data operations. Before joining LiveRamp, Shreyas served as a Data Scientist and Engineer at Data Plus Math, where he built and implemented multiple data pipelines for various clients. He improved impression, reach, and attribution metrics, effectively wearing multiple hats in data science, engineering, DevOps, and product management. His contributions included automating system maintenance and data workflows with Bash shell scripts, reducing manual errors by 40%. Prior to this, Shreyas worked at TiVo for over two years as a Data Scientist and Engineer. He developed predictive models using Random Forest algorithms to forecast user-level TV viewership probabilities, improving model accuracy by 30%. He also designed predictive analytics solutions with linear regression to forecast TV ratings, helping shape programming and advertising strategies. His work in data modeling and processing large-scale data, including building hybrid advertising models and engineering Scala Spark ETL pipelines, optimized query performance and improved overall system efficiency. Shreyas’s academic foundation includes a Master’s degree in Computer Science from Northeastern University, where he specialized in machine learning, algorithms, and parallel data processing. He worked on projects like "Fighting Crime with Big Data," developing predictive tools using Hadoop and AWS. During his internship at Novartis, Shreyas built a Principal Component Analysis (PCA) tool on Spark, enabling analysts to work with large datasets effectively. Shreyas has earned several certifications in machine learning and deep learning from Coursera, reflecting his commitment to continuous learning. With a strong foundation in data science, engineering, and product development, Shreyas is a dynamic professional who continues to deliver impactful solutions at the intersection of technology and business.

• SQL
• JavaScript
• Python
• Database Management
• Hadoop
• Apache Spark
• Data Visualization
• Principal Component Analysis (PCA)
• Linear Regression
• Data Plus Math
• AWS (Amazon Web Services)
• Bash Shell Scripting
• Random Forest Algorithms
• DevOps Practices
• Data Pipeline Automation
• Machine Learning Frameworks
• Reporting Tools
• Parallel Data Processing
• Large-Scale Data Workflow Management
• Cloud-Native Data Engineering
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