Sidharth Dugar

About Sidharth Dugar

Hello, I am Sidharth Dugar, a results-oriented individual with 3 years of experience in data analytics, data science, and machine learning. Currently, I am pursuing a Master\'s degree in Applied Analytics from Columbia University, with an expected graduation date of May 2023. I hold a Bachelor\'s degree in Computer Science from BML Munjal University. Throughout my career, I have worked collaboratively in cross-functional teams as well as independently to develop machine learning models, build APIs for computer vision applications, and automate report generation. I have expertise in various technical skills such as Python, SQL, R, Power BI, Tableau, Alteryx, and PySpark. Additionally, I have hands-on experience in data management, data wrangling, and statistical analysis. My track record of success includes improving the process efficiency for K1-Tax form filing by 30%-40% during my tenure as a Business Technology Analyst at Deloitte. In my current role as a Marketing Analytics Intern at Columbia University, I developed an email marketing campaign that increased the average click-through rate by 3% and reduced data mining and storage time by 45% through automation scripting. I am also adept in programming automation scripts and developing real-time analytics dashboards to inform decision-making for management. I received the Deloitte Spot Award for my work attitude, discipline, and collaboration with external vendors. In addition to my technical skills, I possess strong soft skills, such as analytical thinking, problem solving, strategic thinking, communication, storytelling, interpersonal skills, and collaboration.

Experience

1. Data Scientist Lead

   Deloitte

   Jun 2023 — Present · Jersey City, NJ, US

   Built an end-to-end agentic system to extract structured data from complex tax forms (K-1, K-3), improving data extraction accuracy from 70% to 92% and reducing processing time per file from 10 mins to under 3 mins; greatly enhancing tax professionals’ speed and efficiency.Led integration of Generative AI and LLMs to automate indirect tax analysis, reducing manual effort by 90% and improving accuracy from 60% to 85%, helping clients secure significant tax refunds.Designed and developed a multimodal approach using vision models for invoice and tax bill analysis, improving extraction performance from 75% to 85%, saving $300K annually.

Education

• Columbia University

  Master of Science - MS, Computer and Information Sciences (Analytics)

• BML Munjal University

  Bachelor of Technology, Computer Science

  2016 — 2020