Alan Gray LLC was established in 1988 as a claims and audit advisory firm, and over the years has built a reputation as a cost-effective, reliable, and trusted resource to those involved in the management of risk. Providing operational and business processing services, and consulting on risks and exposures from the simple to the most complex, we place the utmost emphasis on client service and satisfaction. We have become an adviser and partner to a client base that includes major insurers and reinsurers, Fortune 500 companies, law firms, MGAs, brokers, and captives.Our goal is to help our clients realize significant bottom-line savings as a result of our highly experienced technical staff, our ability to adapt quickly to situational changes, and our commitment to staying current with the latest industry information and advances in technology.

•Collect, clean, and maintain datasets and databases. Extract and link data from multiple databases for analysis. Prepare detailed documentation. •Develop models and implement program code (STATA, Python, SQL, R, SAS, Matlab, etc.). •Perform statistical analysis, including regression analysis and machine learning techniques. •Assist with data analysis and dissemination of findings through the preparation of reports, journal articles, presentations, websites, and other research outlets. •Perform case-based research, including work with detailed primary documents.

Public Pensions and Retirement Security in the U.S

1. Conducted thorough analysis of current customer volumes to glean insights into market trends, enabling informed strategic decision-making.2. Collaborated closely with customers, reviewed contracts, and engaged with logistics teams to proactively understand and anticipate customer needs.3. Assisted in marketing AI products through thought leadership that helped in closing 3 deals globally.4. Stepped in as backup for Product Movement Analysts in the Logistics group, maintaining operational continuity during absences.

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1. Collected, analyzed, and meticulously input marketing data into CRM and reporting tools to facilitate strategic decision-making.2. Conducted in-depth analysis of marketing campaigns, encompassing digital advertising and social media efforts, evaluating effectiveness and pinpointing areas for enhancement.3. Leveraged advanced statistical modeling and analytics techniques to extract valuable insights, driving informed marketing strategies.4. Orchestrated the creation and management of dynamic marketing dashboards, comprehensive reports, and key performance indicators (KPIs), ensuring real-time monitoring of marketing metrics and timely updates for stakeholders.5. Generated, assessed, and interpreted information from diverse reporting tools, including Microsoft Dynamics 365, and other internal and external sources.6. Strengthened the marketing team by performing comprehensive market research, strategically analyzing business and marketing landscapes, and accelerating the growth and profitability of a rapidly expanding company within a dynamic environment.7. Pioneered process improvements by identifying opportunities through meticulous analysis, and actively participating in the development of streamlined business processes.8. Collaborated seamlessly with cross-functional teams including marketing, sales, and product, seamlessly gathering data requirements and ensuring impeccable data integrity throughout various systems.9. Assisted in special projects and other assigned duties, contributing to the company's agility and adaptability in a rapidly evolving market.Key Achievements:Enabled a 20% increase in marketing campaign effectiveness through rigorous analysis and optimization strategies.Played a pivotal role in the successful launch of an innovative marketing dashboard, enhancing visibility into critical KPIs for executive stakeholders.Tools Utilized:Access, SQL, Dynamics CRM, Business Objects, Google Analytics, Power BI

• Collaborated with cross-functional teams to collect and analyze data requirements, resulting in moreeffective data-driven decision-making processes.• Data cleansing and transformation procedures were carried out to ensure data accuracy andconsistency.• Complex SQL queries were created for retrieving and analyzing huge datasets from diversedatabases.• Tableau and Power BI were used to create aesthetically appealing and interactive dashboards forexecutive reporting.• Predictive modeling was used to optimize sales forecasting using machine learning algorithms,resulting in a 15% increase in revenue.