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

<p>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.<br>
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.<br>
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.<br>
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.<br>
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.<br>
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.<br>
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.<br>
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.<br>
Analyzed data from 100 cake samples to determine the business consumer impact of factors such as sweetness, color, and taste on consumer satisfaction.<br>
Conducted cluster analysis to segment customers based on their purchasing behavior and preferences, enabling targeted marketing strategies for different consumer segments.</p>

<p>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.<br>
Implemented clinical data analysis using SPSS, resulting in a 25% reduction in research project completion time and a 15% increase in accuracy of findings.</p>

<p>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.<br>
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.</p>