Cathy Bangos

*Defined, analyzed, and solved complex business problems relating to area of market research
• Formulated mathematical and predictive models to enable scenario planning for better performance in Market Research industry
• Applied mathematical models to experimental observations, and perform necessary recalibration of the models to ensure better predictive performance
• Identified growth opportunities through mathematical and statistical analysis
• Specified the data to be collected, the methodology to be used, and evaluate the reliability and authenticity of source information
• Gave mathematical and statistical assistance particularly on sampling, segmentation, market studies, innovations, pricing, driver analysis, and public opinion research

Developed and implemented 15 mathematical and predictive models, including regression analysis and predictive modeling techniques, resulting in a 25% increase in the efficiency of market studies and a 20% improvement in the accuracy of public opinion research.
Generated daily, weekly, monthly, and yearly analytical reports using MS Power BI and MS Report, which facilitated a 360-degree assessment of key performance indicators (KPIs), leading to informed decision-making at all levels.
Leveraged SPSS, SAS, and advanced regression analysis techniques to conduct quantitative and qualitative analysis of consumer behavior, leading to the identification of market trends and opportunities.
Trained and mentored junior analysts in statistical methodologies, including regression analysis and predictive modeling, resulting in a 20% improvement in project completion time and a 15% increase in client satisfaction scores.
Contributed to the development of standardized procedures and templates for data analysis, including regression analysis, predictive modeling, and market segmentation, streamlining workflow processes and reducing project delivery time.
Conducted factor analysis to understand the underlying dimensions influencing consumer preferences and behaviors for clients like pH Care company, resulting in targeted marketing strategies and product positioning.
Utilized multi-level modeling techniques for different projects, tailoring statistical models to account for hierarchical data structures and nested relationships, resulting in a more accurate representation of complex phenomena and providing actionable insights for targeted interventions and strategic decision-making.
Analyzed the perceived value for money of products through comparison with competitor offerings, incorporating pricing data and customer feedback, leading to a 10% improvement in customer satisfaction scores, with an increase of 200 points on the satisfaction index.
Analyzed data from 100 cake samples to determine the business consumer impact of factors such as sweetness, color, and taste on consumer satisfaction.
Conducted cluster analysis to segment customers based on their purchasing behavior and preferences, enabling targeted marketing strategies for different consumer segments.

Consulted an intensive program presenting and reporting advanced 23 statistical methodologies (Multivariate Analysis, Time Series Analysis, Bayesian Statistics) to over 500 student researchers, fostering a deep understanding of complex research challenges.
Implemented clinical data analysis using SPSS, resulting in a 25% reduction in research project completion time and a 15% increase in accuracy of findings.

Developed and implemented multilevel models in consumer acceptability surveys, enabling the prediction of product performance and understanding consumer preferences to a 20% increase in predictive accuracy for product performance.
Analyzed consumer survey data using advanced statistical techniques, uncovering key factors influencing product acceptability and consumer preferences, resulting in a 15% improvement in product satisfaction ratings, with an average increase of 2 points on a 10-point scale.