Senior Research Analyst – City Stats Nov 2020 – Mar 2023
As lead research analyst, guided researchers in developing research tools for Market Research, Business Intelligence, and processes for analysis, including grant-funded studies, while identifying key data sources and managing expectations from diverse stakeholders.
- Successfully mentored and guided core team of 3-4 professionals in business and data analytics in over 1,000 individual tasks and projects, significantly fostering professional growth and development.
- Meticulously trained research teams to collect primary and secondary quantitative and qualitative data through structured and unstructured interviews, desk research, and surveys.
- By diligently defining research scope, deliverables, and work plan in coordination with stakeholders, expertly led cross-functional research teams to complete 4 market research projects, and successfully grossed $145,000.
- Expertly provided tailored solutions in business intelligence, leveraging API queries and SQL to build real-time data integration dashboards, pooling data from SQL/ MySQL databases, while successfully generating over $175,000 in consulting and research fees.
Statistical Data Analyst – Eurosig Oct 2015 – Oct 2020
As a statistical data analyst in insurance, collected and analyzed data to conduct statistical modelling for risk management and premium forecasting, providing management with regular reports for informed decision-making
- Strategically conducted advanced longitudinal data analysis using R – programming and Stata, critically analyzing results, and presenting findings in reports to forecast market premiums with a 95% degree of accuracy, thereby enabling data driven decision-making and informed risk management
- Conducted advanced analytics and data visualizations summarizing historical sales data by agents into comprehensive Excel reports, thereby enabling critical analysis to identify issues, and propose appropriate recommendations, resulting in 20% reduction in costs
- Systematically tracked, analyzed and modelled large sets of public data from the Supervisory Financial Authority and Central Bank to monitor long-run trends in the insurance market, reliably ensuring that market statistics adhere to predetermined benchmarks
- By expertly creating and implementing comprehensive data policies across 5 organization departments, successfully combined technical staff training with effective data governance awareness and communication, thereby significantly slashing policy administration processing times by 50%
Statistical Data Analyst – UnitCenter Jul 2017 – Jan 2020
As statistical data analyst, collected data, conducted statistical analyses, interpreted results, and presented findings in reports tailored for diverse audiences, while offering actionable recommendations to management.
- Ably supervised a professional team in business and data analytics as part of day-to-day work plan, thereby ensuring smooth operations
- Compiled and maintained portfolio of over dozen recurring dashboards in Power BI and Excel by utilizing SQL and DAX to pool call metrics across 3 CRM systems, successfully covering key business areas in sales, HR, operations and finances
- Collaboratively worked with floor and operational managers to diligently optimize call center metrics, resulting in doubling of agent productivity within first two years
INDIVIDUAL PROJECTS
- Diligently collected property data from public listings through dynamic web-scraping and utilized machine learning and multivariate regression models in R – programming to successfully estimate factors that influence the commercial real estate market
- Applied natural language processing (NLP) techniques, including sentiment analysis and topic modelling (LDA), to analyze a dataset of 13,000 negative user comments on Amazon's Alexa, uncovering the main areas of concern thereby enabling better customer service capabilities
- Implemented a robust quantitative framework that leveraged machine learning classifiers, including random forests and logistic regression models to efficiently detect potential cases of financial and insurance fraud increasing compliance by 75%
- Utilized statistical modelling techniques and Monte Carlo simulations to estimate risk exposure in construction projects by employing the triangular distribution and leveraging the central limit theorem (CLT)
