Melody Teng
About Melody Teng
Melody Teng is a Data & Reporting Analyst in Strategic Planning & Delivery at MassMutual, with a background in data science and marketing.
Current Position at MassMutual
Melody Teng is currently working as a Data & Reporting Analyst in the Strategic Planning & Delivery division at MassMutual in the Springfield, Massachusetts Metropolitan Area. She leverages her analytical skills to support strategic decision-making processes within the company. Her expertise includes data visualization, predictive analytics, and data migration, all of which play a crucial role in her current position.
Previous Experience at Galvanize Inc
Prior to her role at MassMutual, Melody Teng worked as a Data Science Fellow at Galvanize Inc in the New York City Metropolitan Area for a duration of three months from 2020 to 2021. During this period, she gained valuable experience in advanced data analysis and machine learning, which contributed significantly to her professional development in the field of data science.
Marketing Specialist Roles
Melody Teng has a diverse background in marketing, having worked as a Marketing Specialist at multiple organizations. She was with Hinton Information Services in Taipei City, Taiwan from 2019 to 2020, and held similar roles at Logos in the Greater Los Angeles Area and ISM in the San Francisco Bay Area in 2018 and 2019. During her time at these positions, she developed and executed marketing strategies that supported business growth and market presence.
Educational Background
Melody Teng completed her Bachelor of Arts (B.A.) in History at the University of California, Los Angeles from 2012 to 2016. She also attended Taipei American School, where she laid the foundation for her academic and professional journey. Her education has provided her with a solid grounding in analytical thinking and research skills, which she continues to apply in her career.
Technical Projects and Contributions
In her roles, Melody Teng has led several impactful technical projects. She developed a comprehensive data visualization dashboard using Tableau that improved strategic decision-making. She also utilized Python libraries like Pandas and Numpy to streamline data workflows, cut processing time by 30%, and implemented machine learning models with SKLearn, increasing customer retention rates by 15%. Additionally, she contributed to a company-wide data migration initiative and built interactive visualizations with Seaborn for executive presentations.