The power of data science isn't just for large companies with vast resources. Small companies and businesses can also benefit from data-based decision making. I founded Alhazen Business Intelligence Consulting to democratize this field and help businesses leverage data science for better profits.I excel at communicating the capabilities of data science and the foundation needed to implement it effectively. This includes:✔ Developing sound data science processes ✔ Incorporating the right tools ✔ Empowering staff to perform and interpret the analyses Implementing a data-based business strategy can also involve a major cultural shift within a business. I'm fully adept at understanding a company's specific culture, and I tailor communication and implementation strategies accordingly to achieve success.Key Achievements:✔ Introduced predictive modeling benefits to mid-sized biotechnology and healthcare businesses for improved operational efficiency and scalability✔ Incorporated predictive modeling techniques for financial forecasting for better-targeted business plans, pitch decks and financial models for healthcare industry startups

Students' college years contain a lot of transition and uncertainty, but Optimal Property Management provides a base where students can ground themselves and have a safe, comfortable and well-managed home.Located in the town of Hamden area, Optimal Property Management is highly regarded by both property owners and tenants for its quality service and responsiveness. Our exceptional focus on customer satisfaction and operational efficiency sets us apart from other property management companies and makes us the go-to resource in the area.As an Owner and Founding Partner, I optimized our property purchasing through predictive analytics and customized application development using Google Maps API and Java. I also used my relationship management skills to develop strong business partnerships and high customer satisfaction metrics.Key Achievements:✔ Development of proprietary software and analytics for pre-purchase property assessment✔ Asset growth of over $.8M in less than 21 months with ITD revenue nearing $1M✔ Occupancy rate of 99% since inception

Machine learning, blockchain data and Web3.0 technologies combine to create a compelling opportunity for predictive analytics to individualize the user experience and drive product innovation in decentralized finance and blockchain in general. Bird.Money is developing data-driven solutions used to analyze the blockchain, with its first prediction product, the Blockchain Individualized Risk of Default (BIRD) Score , designed to allow DeFi lenders to offer undercollateralized loans by improving upon the legacy financial system’s credit score. The BIRD Score is the first DeFi credit score based on the statistical prediction of loan default, created using advanced machine learning methods and made available to lending protocols as a simple, accessible rating via the decentralized Bird Analytics Oracle. It’s the next generation of credit scoring. Also currently under development is a similar launchpad score that empowers IDO providers to offer funding options optimized to support a project in its early stages. By varying IDO token price and vesting schedules based on wallet-level predictions of supportive behaviors such as long-term holding or liquidity provision, startup projects can ensure the greatest likelihood of success.

I'm leveraging robust technologies to introduce data science initiatives at Boca Biolistics, a company that provides research services to In-vitro diagnostic manufacturers.I lead multiple teams consisting of data analysts, licensed medical technicians, laboratory technicians, sales associates, and other administrative staff. My teams have improved productivity through efficiency gains garnered from data-driven systems and decisioning. As a manager, I learn what incentivizes each team member, and I structure projects to accentuate their motivational drivers. This technical approach to management ensures we achieve our goals.One area where we've achieved great success is developing systems based off principles of behavioral economics for better individual development and for employee recognition. This allows management to get a complete picture of employees' performance and better recognize their achievements.Key Achievements:✔ Designed, built and implemented a company-wide ERP system, colocating all business-critical data to facilitate improved operational analytics✔ Instituted software-driven sales systems/tools leading to a 53% YOY increase in closed orders ✔ Automated and outsourced data capture, resulting in an 80% cost reduction and improved accuracy✔ Designed economic cost basis model for acquisition channels, approaching true first-degree price discrimination

At Google I had the opportunity to contribute to the company's mission to make information universally accessible and useful through innovative data science modeling.I led the development efforts on two projects that harnessed data in a way that hadn't been done before and worked with teams to provide our clients with data-fueled analysis that allowed them to make better business decisions that led to enhanced strategies and better margins. I worked in collaboration with our clients' technical teams, my fellow Analytical Leads and Engineering to introduce predictive analytics, offer statistical computing training and help develop or evaluate new tools. I was instrumental in enabling the use of existing Google tools such as AdWords and Google Analytics to develop new, innovative statistical procedures. This allowed us to quantify complex, high-impact opportunities for our clients. I presented our model output and actionable strategies to client leadership, including Executive Teams and high-level leaders at Fortune 100 companies, and at conferences such as YouTube Data Days.Key Achievements:✔ Led development of the first-ever time-series models forecasting sales/online traffic to less than 3% error for Executive Team at a major international auto manufacturer ✔ Led the development of time-series impulse response functions that were the first quantification of the decay rate of increased social activity after homepage advertising presented at the Youtube Data Days conference

At Travelers I was a data science leader who implemented data science techniques and introduced econometric analysis to our Business Insurance unit. This allowed Travelers to harness the power of data science to make sound business decisions, a crucial strategy coming off of the financial recession.To empower our data science efforts, I:✔ Determined the necessary infrastructure✔ Understood and encouraged the necessary cultural changes✔ Obtained the necessary resources to empower the data science I managed a staff of up to 5, including PhDs and SAS programmers and was responsible for managing workload and performing reviews. Additionally, I was a member of Travelers Econometrics Leadership Council, a group that set company-wide strategy for economic analysis. Through this group I established an enterprise-wide, conceptual framework for evaluation of all project strategy.Key Achievements:✔ Introduced advanced econometric methods to forecast key trends as part of business performance planning and contingency analysis✔ Invited to present the latest research in the field of Behavioral Economics to top analytic leadership in order to propose strategic recommendations covering B2C efficacy, the psychology of analytics and human resource management✔ Led development of innovative SAS-based reporting and analysis applications for use across the analyst community

I managed our actuarial research efforts, integrating cutting edge statistical tools and techniques with traditional actuarial methods to achieve company objectives for reserve adequacy and analytic growth in the domain.I also led various projects and managed direct reports, including furthering their professional development through performance reviews and creating individual development plans.Key Achievements:✔ Fostered innovation by introducing advanced statistical methods, such as kernel smoothing and logistic regression, within traditional actuarial techniques and by utilizing SAS to integrate highly-detailed transactional loss data✔ Led consumer analytics project focused on correcting and enhancing retention forecasts using linear regression and outlier mitigation techniques to meet predictive accuracy objectives for SEC reporting✔ Led technical design and 5-person development team in creation of automated loss report and analysis suite that reduced report generation and validation time by more than 99% in phase 1, i.e. 8 hrs. reduced to 2 mins.✔ Instituted an MBA internship program with Quinnipiac University to provide opportunities for students on scholarship from Central Europe and bolster Travelers' talent pipelines

I managed statistical programming for predictive model development using advanced data mining techniques and software in order to solve critical business problems, drive underwriting strategy and enhance business operations.Additionally, I served as Director of R&D's Internship program and was responsible for hiring 26 interns into 7 departments through coordination of 41 interviewers and 1 full-time recruiter. I also directly managed our PhD interns and encouraged their professional development by completing performance reviews and creating individual development plans.Key Achievements:✔ Led customer lifetime value analysis through development of survival models specially adapted to the direct-to-consumer acquisition channel in order to guide marketing expenditure✔ Led a team of 4 analysts in designing a SAS-based monitoring infrastructure for credit scoring model that was developed over 7 years with a budget in excess of $5M✔ Instituted key operational efficiencies in intern recruiting program that reduced the number of interviews per hire by 20%

As Travelers began implementing data science within its business units, my role was to help employees understand the principles behind using our work help the business make decisions out of the work. I assisted in statistical programming for predictive model development, and I used advanced data mining techniques and software in order to solve critical business problems, drive underwriting strategy and enhance business operations.Key Achievements:✔ Conducted agency performance analysis through primary research from over 2000 principals, sales agents and executives to provide recommendations that led to product design innovations✔ Developed logistic regression models in SAS to identify residential structures that are most likely to be under-insured, which were used to optimize operations expenditure✔ Developed residual pure premium double-generalized linear models in SAS to re-build the Massachusetts auto insurance pricing plan following partial market deregulation