Palvika Bansal
About Palvika Bansal
Palvika Bansal is an NLP Research Scientist at Thomson Reuters in Bangalore Urban, India, where she has worked since 2021. She has a strong background in machine learning and analytics, with previous roles at Samsung Heavy Industries and PwC, and holds multiple postgraduate diplomas in business analytics from prestigious institutions.
Work at Thomson Reuters
Palvika Bansal has been employed as an NLP Research Scientist at Thomson Reuters since 2021. Based in Bangalore Urban, Karnataka, India, she has contributed to various projects focusing on natural language processing. Her role involves applying machine learning techniques to enhance the company's data analytics capabilities.
Previous Experience at Samsung Heavy Industries
Before joining Thomson Reuters, Palvika Bansal worked at Samsung Heavy Industries as an Analyst from 2014 to 2017. During her tenure in the Noida Area, India, she gained valuable experience in data analysis and problem-solving within the industrial sector.
Education and Expertise
Palvika Bansal holds a Post Graduate Diploma in Business Analytics from the Indian Institute of Technology, Kharagpur, and has also completed a Post Graduate Diploma in Business Analytics, Mathematical Statistics, and Probability from the Indian Statistical Institute, Kolkata. Additionally, she earned a Post Graduate Diploma in Business Analytics from the Indian Institute of Management, Calcutta. Her educational background equips her with a strong foundation in machine learning and statistical methods.
Skills and Technical Proficiency
Palvika Bansal possesses expertise in implementing machine learning algorithms, including Random Forest and XGBOOST. She is skilled in various tools and programming languages such as R, RShiny, Python, SQL, Alteryx, and Tableau. Her technical proficiency supports her work in data science and analytics.
Experience in the Energy Sector
Palvika Bansal has worked in the energy sector, specifically optimizing instrument selection for Oil & Gas clients. This experience highlights her ability to apply analytical skills to industry-specific challenges, contributing to improved operational efficiency.