https://dream.weekday.works/redirectToHiringCopilotExtension/

Red Hat

In-Q-Tel

Intel

Altimeter Capital

New Enterprise Associates

Goldman Sachs

Sequoia Capital

Salesforce Ventures

T. Rowe Price

Flybridge Capital Partners

Union Square Ventures

Benchmark

TriplePoint Capital

TrueBridge

Kaplan Group Investments

AlleyCorp

Vaidya Capital Partners

Sozo Ventures

Syren Capital Advisors

Section Partners

Dell Technologies Capital

Janse Capital

OGGI Equity

Ringway Capital

HTIF

Madica

Cloud based provider of NoSQL database software. The platform uses distributed infrastructure on commodity servers and is popular with developers for building mobile and web applications. The features of the product include data visualization, cluster distribution, etc.

Cloud based provider of NoSQL database software

Accel

Wellington Management

Arctos Sports Partners

Ryan Smith

Utah Jazz

Glynn Capital

Haystack Partners

Causeway

Medici Firma Venture

QueensBridge Venture Partners

FJ Labs

Red Swan Ventures

Founder Collective

NYC Seed

Entree Capital

A-Grade Investments

Stage One Capital

PKS Capital

Brainchild

Arie Abecassis

Sunil Hirani

Thomas D Lehrman

Mark Wachen

Allen Levinson

Dreamit

Foundry Group

Future Perfect Ventures

Upstage Ventures

Teamworthy Ventures

Lerer Hippeau

Sound Ventures

Value Investment Group

Finger Group

Elysian Park

Cherry Tree

Phase 2 Investments

Eversource Capital

Foundry

SeatGeek provides search and price forecasting for consumers purchasing sports, concert, and theater tickets on the secondary ticket market. SeatGeek mines ticket transactions from secondary ticket markets including Stubhub, TicketNetwork, TicketsNow, and Razorgator, providing a search of the secondary ticket marketplace in one search. SeatGeek has a feature called Deal Score that assigns a 0 to 100 metric to all listed tickets in order to ascertain the relative value of tickets for a given event or set of similar events.

· Converted scripts from bash to Python to improve the code’s robustness
· Refactored code by modularizing it and simplifying it for increased maintainability
· Implemented extensive unit tests with Python’s unittest framework to ensure correctness of code
· Debugged and fixed errors in Python scripts by setting up breakpoints using pdb (gdb style debugger)
· Conducted thorough code review to remove bugs and increase performance and readability of code

· Utilized MongoDB to create an efficient map API for integration with the Skopenow web application
· Designed an algorithm for nickname and fuzzy name detection using analysis of phonetics
· Analyzed key data on web pages for use in algorithms and database population
· Processed data from the Instagram API in order to make the people search algorithm more accurate

Skopenow mitigates insurance fraud by searching the internet for claimant's social media footprint. It is a risk assessment tool used for underwriting by insurers and insurance carriers. It provides an API which can be integrated into the client's website.

Social media based fraud protection solution.

Designed efficient algorithm that analyzes JSON data containing bus schedule information and finds routes between locations in the Binghamton and Vestal area. Retrieved data from SQL database to run the algorithm on. Designed the flow and layout of mobile application in order to create a better user experience. Utilized Adobe's PhoneGap so that the application could be deployed on various mobile platforms using only one set of code. Debugged and tested application in order to fix remaining bugs and provide users with a polished application

Software Engineer at MongoDB

rushil kumar