Prakhar Kumar

With over 13 years of experience as a Technical Manager, I specialize in AI/ML, NLP, Python, RPA (UiPath), and .NET technologies. I lead high-performing teams, delivering scalable solutions across industries. My AI and ML expertise drives data-driven decisions, while my NLP skills enable advanced language models for sentiment analysis, keyword extraction, and language translation. Proficient in Python, I design automated workflows ensuring efficiency. My RPA experience with UiPath automates complex processes, reducing costs and boosting productivity. A strong .NET foundation allows me to build secure, scalable applications, integrating seamlessly with enterprise systems. My technical acumen and strategic mindset consistently meet and exceed client expectations. Passionate about technological advancements, I continuously enhance my skills to drive innovation and deliver impactful solutions.

• PL 900 & PL 500 , 2024
• AHM 250 , 2024
• Project Management Professional - PMP, 02/2023
• Advanced Certified Scrum Product Owner, 12/2022
• Lean Six Sigma Black Belt, 10/05/2020
• Scrum Master (CSM), 12/08/2020
• Advanced level 3 UiPath Certification, 01/20/2019
• MCSD 70-486(Developing ASP.NET MVC Web Applications), 05/28/2016
• MCSD 70-487(Developing Microsoft Azure and Web Services), 04/23/2016
• MCSD 70-80(Programming in HTML5 with JavaScript and CSS3), 03/05/2016
• MCP 70-532(Developing Microsoft Azure Solutions), 02/17/2016
• MCTS 70-536(TS: Microsoft .NET Framework – Application Development Foundation), 07/30/2012

• Successfully delivered 50+ projects in different domains (Healthcare, Banking, Automobile, Oil & Gas Industry and FMCG).
• Single handed managed Provider and Contact centre vertical to yield best FTE Savings in a challenging environment and conditions.

Technology used: NLP using BERT, Python, Dot Net Core   Role: Technology/Delivery Manager

Description: Developed an NLP model for policy mapping between EIS and industry standards like HiTrust and ISO. Utilizing BERT, the application suggests similarities between statements and employs a concise similarity index to calculate textual similarities. This automation significantly reduces manual effort and time for the EIS team.

Phycon Nice Automation (Provider)

Technology used:UiPath, Dot Net

Description: The purpose of this automation is to process end to end Phycon request for Provider demographics update. NDB used as source as truth to get the provider's demographics information. Automation update this information in Nice and ProBase based on the business rules provided and bot completes the Phycon request with appropriate comments. Inventory provided by the business as an excel file for automation as input.

Technology used: UiPath, Dot Net, Fuzzy Logic(ML) for Address Matching Role: Technology/Delivery Manager

Description: The solution involves multiple sources for keep providers data updated in NDB. Agents make calls manually to get the updated information from Provider and then NDB and onBase updated by agents manually. We have created automation to Automate NDB and OnBase update as well as provided alternative source as Provider verification link and auto-mail for reducing calls made to providers and streamline the process. We have used ML for address matching using Fuzzy Logic and to get correct address formats to be saved in NDB.

On Call Assistance (Contact Center)

Technology used: WPF, WCF and MS SQL

Description: This product created to help Contact Center agents while they are on call they do not need to refer to lengthy SOPs and they can get the steps need to be performed on the call in the tool. This tool is highly configurable and changes can be made by business users without any involvement of development teams. This is deployed across in multiple LOB and teams and provided efficient savings.

Description: Automation works on reimbursement requests from employees for broadband bills in Concur application. Automation works for 6 different providers and picks the data elements from the bills. Run business rules on those data elements to find out the request can be approved or it should go back to employee. Bot provides a report to agents with the analysis.