Maya Avida

Data Science Intern @ SPAN

About Maya Avida

Maya Avida is a Data Science Intern currently working at Tiger Capital Management and SPAN, focusing on machine learning and optimization techniques. She is pursuing a Bachelor of Arts in Physics at Princeton University, where she also conducts research and maintains a GPA of 3.98.

Work at SPAN

Maya Avida serves as a Data Science Intern at SPAN, a position she has held since 2024. In this role, she focuses on utilizing machine learning and optimization techniques to forecast home electrical load. Her work aims to optimize electricity consumption and improve rate plan structures. This internship is based in San Francisco, California, and is part of her ongoing professional development in the field of data science.

Current Role at Tiger Capital Management

Maya Avida is currently employed as an Analyst at Tiger Capital Management, where she has been working since 2023. This role is located in Princeton, New Jersey, and involves on-site responsibilities. Her experience at Tiger Capital Management contributes to her analytical skills and understanding of financial data.

Education and Expertise

Maya Avida is pursuing a Bachelor of Arts in Physics at Princeton University, with an expected graduation in 2026. She is also minoring in sustainable energy, statistics, and machine learning. Her academic performance is notable, with a GPA of 3.98/4.0 in her major. Prior to her university studies, she graduated from The Nueva School with a High School Diploma in 2022.

Previous Experience at Malta Inc

Before her current roles, Maya Avida worked as a Project Intern at Malta Inc for two months in 2020. This position was based in California and provided her with early exposure to project-based work in a professional setting. This experience helped her build foundational skills relevant to her current career path.

Research Role at Princeton University

In addition to her internships, Maya Avida has been working as a Student Researcher at Princeton University since 2024. This role, which she has held for eight months, involves on-site research activities that complement her academic studies and enhance her practical skills in data science.

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