Cognome is revolutionizing the way healthcare data is used to transform care delivery, clinical operations and medical research. Cognome’s work began at the University of Texas in 2010 and continues today at Montefiore Health System and Albert Einstein School of Medicine in New York City. Cognome provides AI and ML models and an ensemble of LLMs purpose built for next-generation clinical decision support, precision medicine and operations optimization. For researchers, data scientists and AI developers, Cognome offers an entire ecosystem for clinical innovation. 10+ years of continuous R&D, 7 patents and proven, real-time ML models utilized by 20+ hospitals make Cognome the leading provider of healthcare AI and ML models.I'm working to revolutionise and improve the healthcare industry utilising technology and advanced AI-ML techniques as a Product Manager

- Product Manager cum Owner for 2 product lines - DSA + Backend- During my tenure, the number of users scaled 6x from ~100 users a month to 500-600 users a month with weekly revenue numbers hitting 2 cr.- Worked across the Product Lifecycle - From onboarding users after-sales -> user journey through the content -> referral cycle- Thriving in uncertainty and impact was huge on a daily basis. - Major updates in the funnel - Added Plagiarism checks for Code - Grading implemented and now being improved for learners - Scaling the product while catering to optimising the job a user gets based on their interest and also is job ready- Referral pool bottleneck - improved job outcomes for DSA interviews from 33 to 50%- Started a new initiative now for FSD+ (SDE -2 users ), wrote PRDs for the same and did detailed Market and Competitor analysis for the same- Team structure - worked with Engineering, Content team, Designers, Curriculum delivery, Sales & Outcomes

*We do all the hands-on and unglamorous work of a Product Manager/Owner on an Interim basis (3-12 months). We can also make pretty decks but prefer to deliver outcomes. We give back to our community of 7K+ Product Managers through weekly events and knowledge-sharing.**Some people refer to this as "Freelance." We're a GmbH, and our people are full-time employees. So our clients are protected from the liability of working with freelancers while getting the benefit of having the same contact person.*Team Deck - https://docs.google.com/presentation/d/1u_5YZkLJ9UN9rLo8qCQiZvuqukpnfXkfFTSv95ADY5w/edit?usp=sharing

As part of user platform engineering, I contribute to various small and large projects (backend) to support internally used platforms within the firm.Created an automation packaging application in 2 months, to create .msi file, bundling the .exes and dependent files which reduces manual effort on the Support team by 18%.Subject matter expert of the application keeping track of all the virtual machines and user mapping data at the firm.Built an automation system for scripts in 6 months for files to be deployed on desired machines from which they can be run on autosys at a required frequency, reducing manual deployment time by 10x.

Worked on the product NetBackup to provide the functionality of backing up, storage and recovery of MongoDB files.

• Worked with the Securities and Payment Team in the IOT Division.• The project aimed at generating the call stack to analyse the crashes in the device(smart watch and mobile phones)without the presence of device,but using the .log,.cs and .coredump files generated by it.• Used Shell Script development on linux environment for generating call stack using gdb by analyzing .coredump files.

• Worked with the Web Identity Security Labs team• Understood the usage of Qt5 software by learning basics of QML in applications like finding a mathematical model to explain difference in dynamic texture using 3D color space during the project.• Suggested changes in the content of a Research Paper based on Phishing Website Detection.

•Worked with the Total Quality Management Team and contributed towards Development of Business Analytics Module• Learnt and Applied Lean Six Sigma Methodology on Industrial Data sets• Applying the learned analytics in Business Environment to develop prediction models for given data sets• Learned using Mathematical Software Minitab for implementation• Also used Python libraries like scikit learn, Numpy etc. for prediction models

• Studied some research papers on Computational Geometry, particularly finding shortest paths between points and finding the order of complexity of the problem.• Also tried finding algorithms to reduce the order of complexity for the same.