Maithri Mathew
About Maithri Mathew
Maithri Mathew is an Associate Software Engineer at The New York Times, where he focuses on analytical experiments and data visualization. He holds a postgraduate degree in Data Analytics and Visualization from Rutgers University–New Brunswick and has previous experience as a Market Data Analyst and Global Data Analyst at Bloomberg LP.
Work at The New York Times
Maithri Mathew serves as an Associate Software Engineer at The New York Times, a position held since 2022. In this role, Mathew is part of the business reporting team, where the focus is on utilizing analytical experiments and visualization tools to effectively communicate stories. This position involves exploring data to craft narratives that resonate with diverse audiences, emphasizing inclusivity in communication.
Education and Expertise
Mathew holds a Postgraduate Degree in Data Analytics and Visualization from Rutgers University–New Brunswick. Additionally, Mathew earned a Bachelor of Science (BS) degree from the same institution. This educational background provides a strong foundation in data analysis and visualization techniques, contributing to expertise in the field.
Previous Experience at Bloomberg LP
Prior to joining The New York Times, Mathew worked at Bloomberg LP, where roles included Global Data Analyst and Market Data Analyst. The Global Data Analyst position was held from 2020 to 2021 for nine months, followed by a year as a Market Data Analyst from 2021 to 2022. Both roles were based in Princeton, New Jersey, and involved analyzing and managing market data.
Experience at Memorial Sloan Kettering Cancer Center
Before working at Bloomberg LP, Mathew was employed as a Pilot Project Coordinator at Memorial Sloan Kettering Cancer Center from 2019 to 2020. This role lasted for eight months and was located in the Greater New York City Area. The position involved coordinating pilot projects, contributing to the organization's research and operational initiatives.
Professional Interests
Mathew has a keen interest in learning and improving skills, particularly in exploring new areas within the field of data analytics and software engineering. This commitment to continuous learning reflects a proactive approach to professional development and skill enhancement.