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HiLabs Offers the Highest Salary Package of Rs. 2 Crore in their Campus Hiring to a Woman Candidate from the Indian School of Business (ISB) Tuesday 07 February 2023 06:39 AM UTC+00 HiLabs, a leading provider of artificial intelligence-based data analytics solutions for health plans in the United States has offered a 2-crore salary package to a woman candidate from the Indian School of Business (ISB). The international offer was made on the first day of campus recruitment. During campus hiring for 2022, the company offered a record-breaking 27 offers to highly regarded IIT and ISB students.
Mr. Amit Garg, Chief Executive Officer and Co-founder at HiLabs A total of three international offers have been made across campuses for hires to join HiLabs headquarters in the Washington, DC metro area. In addition to the Rs. 2 crore international offer to a woman candidate, the company has offered ISB students salaries between Rs. 40 to Rs. 60 Lakhs per annum with ESOPs for their India office locations. Also, the IIT India and US offers ranged from Rs. 29 to Rs. 80 lakhs per year for candidates who were hired to join any of the data science, engineering and product management teams at HiLabs. Amit Garg, Chief Executive Officer and Co-Founder at HiLabs said, "Placements are a quantifiable way to measure the quality and value add of students who attend and thrive at an academic institution. We are delighted that HiLabs has performed well in the placements, resulting in record-breaking job offers to these highly skilled and qualified individuals. We are proud to have the ability to go on a hiring spree now, helping students find great opportunities despite the current job market, which has seen large-scale layoffs and an economic slowdown across the tech industry. HiLabs record-breaking campus employment is being driven by our exponential growth and unique culture, which includes giving our fresh graduates opportunities to address real-world challenges on day one and to accelerate their experience and career development. HiLabs is focused on improving data quality. To date, we have evaluated over 36 billion health data records and assisted health plans in detecting and correcting over three million data errors related to provider directories, clinical data, claims operations and value-based care. Those who join HiLabs are highly qualified and understand how to approach challenges in a proactive and innovative manner by utilising some of the most advanced technology."
These new hires will immediately begin working with HiLabs AI-powered data quality platform, MCheck™, to assist health plans to recover billions in lost productivity due to data quality issues. HiLabs has made a total of six product management offers, including an international offer at the Indian School of Business (ISB) campus in Hyderabad, a significant increase from previous years. HiLabs is combining cutting-edge, explainable AI with healthcare-specific business ontologies to vastly improve data quality for its health plan clients across provider data, payment accuracy, clinical interoperability, and value-based care. This unique and valuable approach has earned HiLabs business with three of the five largest US health plans. HiLabs core platform, MCheck™ has performed analysis on over 36 billion health data records, covering over one-fifth of the US insured population. It proactively detects and corrects data errors throughout the health plan enterprise, improving operations and analytics, resulting in significant cost savings and revenue growth opportunities. About HiLabs HiLabs provides artificial intelligence-based solutions to manage health data errors, empowering organizations to run their business operations more efficiently. HiLabs has created a healthcare-focused artificial Intelligence (Al) platform, MCheck™ that automatically detects data errors without human knowledge or input. It is a rare fusion of Al, big data, and healthcare business ontologies built by a team of technologists and doctors. The easy-to-use Al platform helps stakeholders identify hidden errors in their data, reduce costs, and integrate disparate healthcare data to find monetizable insights. ![]() | |
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