Priyanka Ramadas
About Priyanka Ramadas
Priyanka Ramadas serves as the Analytics Lead for Growth at Scale AI, where she applies causal inference techniques and advanced machine learning methods to analyze data. She holds a Bachelor's degree in Electrical and Electronics Engineering and a Master's degree in Business Analytics, and has previously worked in various analytical roles across multiple organizations.
Current Role at ScaleAI
Currently, Priyanka Ramadas serves as the Analytics Lead for Growth at Scale AI, a position she has held since 2023. In this role, she employs causal inference techniques through econometrics to derive actionable insights from data. Her expertise in advanced machine learning techniques, including XG Boost and Light GBM, supports her work in regression and classification tasks. Priyanka's proficiency in big data technologies such as Hive and Spark enables her to manage and analyze large datasets effectively.
Previous Experience at Scale AI
Priyanka Ramadas previously worked at Scale AI as a Business Data Analyst from 2020 to 2023. During her tenure, she focused on data analysis and contributed to various projects aimed at enhancing business operations. Her experience in this role laid the foundation for her current position, allowing her to leverage her analytical skills and knowledge in a growth-oriented capacity.
Educational Background
Priyanka Ramadas earned her Bachelor's degree in Electrical and Electronics Engineering from Government Engineering College, Trivandrum, from 2012 to 2016. She furthered her education by obtaining a Master of Science in Business Analytics from the University of Minnesota - Carlson School of Management, completing her studies from 2019 to 2020. This educational background provides her with a strong foundation in both engineering principles and business analytics.
Technical Skills and Expertise
Priyanka possesses a diverse skill set in data science and analytics. She is proficient in Python libraries such as scikit-learn, numpy, and pandas, which are essential for data analysis and modeling. Additionally, she has experience with data visualization tools like Tableau, enabling her to present insights effectively. Her knowledge extends to anomaly detection and clustering techniques, including DBSCAN and Hierarchical clustering, enhancing her analytical capabilities.
Contributions to the Data Science Community
Priyanka Ramadas actively contributes to open-source projects on GitHub, reflecting her commitment to the data science community. This involvement not only showcases her technical skills but also her dedication to collaborative learning and sharing knowledge with peers in the field.