Co-Founding / Interim Head of Data Science responsible for building out the data science function for an early-stage FinTech company that is transforming the way that residential real estate is transacted. Recruited and managed the team that developed the first-ever set of models capable of assessing title risk in real-time based on structured and unstructured real estate data drawn from a variety of sources. Developed the preliminary models, iterated on results, and presented results to business stakeholders, including re-insurance companies, lenders, and Fannie Mae.
Honorary lecturer at Metis data science bootcamp invited bi-monthly to speak to each Metis SF cohort about the data science field, econometric modeling techniques, and career opportunities in data science. Also advised and mentored individual graduates while exposing students to local hiring opportunities.
Faculty at Singularity University and artificial intelligence expert responsible for following broad industry trends in AI and robotics, placing those developments within a broader learning framework, and presenting that information in an engaging manner to participants in Singularity's executive education programs.
Provided technical expertise, methodological guidance, and best practices advice to help the company leverage its data warehouse in order to reduce customer churn and increase adoption of all technology products. Collaborated with the data science and engineering teams to create and execute on a roadmap for transforming the company into a data-driven organization.
Technical co-founder of a new product that Doma is bringing to market that aims to create a faster, easier, and more frictionless closing process for home sellers:
- Launched a full-stack product (with embedded data science) within 4 months
- Led a team that built out the data science models supporting an MVP to test the uptake, viability, and profitability of an exciting new product.
- Architected the platform and managed the technical infrastructure supporting this new product, leveraging a serverless, micro-services framework with completely automated deployment.
- Recruited, hired, and mentored the initial tiger team of engineers and data scientists responsible for building the platform from scratch and bringing it to market.
Chief Technology Officer responsible for leading the Engineering and Data Science teams and architecting a real-time platform capable of assessing fraud risk for lenders in the automotive, mortgage, and credit spaces:
- Re-architected the platform from the ground up in order to achieve a 5X improvement endpoint response time, 10X improvement in stability and scalability, and a 15-20% improvement in model performance
- Drove forward R&D efforts, prototyped new models, and deployed to production in order to deliver more accurate predictions that enabled customers to save millions through enhanced fraud detection
- Cut down model platform and model deployment time from weeks to hours through the use of automated deployment, continuous integration, and real-time monitoring / testing
Co-Founder and Chief Scientific Officer for RapportBoost.ai, an emotional intelligence engine for conversational commerce. We use machine learning, A/B testing, and closed loop experimentation to help companies understand how best to engage with their customers via chat and messaging interfaces.
- Engineered the core architecture for the system, developed and maintained all databases, and built the platform from a variety of data science tools: Python, Pandas, Scikit-learn, Tensorflow, RabbitMQ, and Django.
- Developed closed-loop analysis and iterated through a variety of state-of-the-art data science models with an eye towards: (1) predictive accuracy of the models; (2) speed of real-time recommendations; and (3) scalability of the underlying platform.
- Explored the viability of a dozens of different external datasets and APIs with the goal of improving the predictive accuracy of the models and the real-time recommendations of the overarching system.
Chief Analytics Officer responsible for engaging in thought leadership, building relationships with University partners, developing intellectual property, and leading all research and development (R&D) activities.
- Engaged in thought leadership by mining client data for unique insights into human resource practices and disseminated the findings through conference presentations, Research Insights, and White Papers.
- Built and managed collaborative relationships with researchers at a half-dozen top tier Universities around the world that yielded presentations at academic conferences, working papers, and journal articles.
- Led all research and development (R&D) activities that created intellectual property and ultimately resulted in a number of provisional and utility patents being filed on behalf of the company.
Chief Analytics Officer responsible for applying econometric techniques to analyze client data, automating reporting / optimization processes, and leading efforts to port this functionality into a scalable SaaS platform.
- Developed new econometric models and methodologies and applied them to client data in order to produce monthly updates of client results and to calculate the value created by Evolv.
- Provided econometric expertise to automate the closed loop optimization process, calibrate the pre-employment assessments, and make them more strongly predictive of employment outcomes.
- Led the team that developed the business requirements, coordinated with Engineering, and performed the QA necessary to port reporting and optimization functionality into a scalable SaaS platform.
Led the firm’s Research and Development (R&D) activities, coordinated all data-related activities, provided scientific expertise, and managed the migration of several core products to the next generation software platform.
- Provided scientific support and insight – methodological, statistical, and analytical – to clients in need of assistance interpreting, disseminating, and acting on organizational data.
- Developed new products, services, and technologies with respect to survey- and observation-based metrics; text mining procedures; data reports, visualizations, and analytics; and statistical algorithms.
- Provided scientific expertise throughout the sales cycle in existing lines of business and identified new opportunities for growth that complemented and extended Pascal’s existing lines of business.
Developed a collaborative research project between the firm's Health Care Advisory (HCA) practice and its Health Research Institute (HRI) measuring the impact of IT implementation on hospital productivity, cost-efficiency, profitability, and quality.
- Analyzed time-series (1998-2005) data on U.S. hospitals (6,000+) from HIMSS Analytics, the American Hospital Association, Medicare Cost Reports, and Thomson-Medstat Medpar databases.
- Drafted written materials in support of the project that included a research methodology, project presentations, outlines, preliminary academic papers, and white papers.
- Managed oversight of the project while approaching potential collaborators, hiring additional personnel, and presenting the research methodology and results to major stakeholders.
Research Analyst II for two years within the company’s Health Care Policy practice and staffed on a number of projects for such clients as SAMHSA, CMS, HRSA, and AHRQ.
- Managed all data-related activities for a project studying the effectiveness of national PASRR requirements, including data collection, statistical analyses, and the development of relational databases.
- Coordinated project activities for the Medicaid Payment Accuracy Measurement (PAM) project by communicating with participating states to organize conference calls, site visits, and quarterly reports.
- Conducted interviews with state Medicaid officers to create a technical guide aimed at instructing states regarding the implementation and financing of Assertive Community Treatment (ACT) programs.