Brett Kramer Email & Phone Number

Dresher, Pa, Us

In my role as a Senior Data Scientist, I am responsible (specifically) for supporting our Retirement LOB. I work as part of a small team/Center of Excellence responsible for providing insights and analytics to the enterprise. I am responsible for both data curation and the entire continuum of data analytics. Within the last year I have begun providing more leadership support, working directly with the Retirement LOB's senior leadership in understanding business priorities to ensure our small but mighty team's work stays aligned to business strategy execution.I have been fortunate to work on and lead:*numerous fuzzy matching projects to harmonize data across the enterprise*predicting the likelihood we would/will win a sales opportunity*predicting the likelihood of each of 578K people enrolling in a retirement plan*Creating metrics to compare customer profitability with suitable peer groupsStay tuned as our team's work broadens and deepens within the organization!

In 2019 I started my own consulting firm offering data science and research expertise specifically to the finance, agriculture, and education sectors where a great deal of my subject matter expertise resides.

Miami, Florida, Us

As Lead Data Scientist, I was responsible for leading and growing a data science practice. I was lucky enough to be able to hire rock-star performers who helped me grow our footprint, and craft and perfect our methodology, approach, and offerings. My team additions were fairly recent, but I have been involved in every single data science project at the firm. Most recently, I was working side-by-side with my team members on a pure financial forecasting project as well as a driver-based forecasting project.I was fortunate enough to serve on many projects and here is a sampling:*4 projects using a data-driven, driver-based approach to predictive financial forecasting*2 large-scale projects (one with over 80K drivers) using Time Series models (ARIMA, ETS, Bayesian, co-Variate) to forecast various measures*Account consolidation using fuzzy-matching logic (Jaro and Levenshtein)*Data monetization and enrichment projects leveraging DnB and Experian datasets*Numerous project using GLM methods for predictive purposes*Several predictive projects using classification methods (RF, Logistic regression, SVM, NN)*A couple of opportunities to apply cluster and factor analysis*Market-type analysis (A-B testing, market basket analysis, lift calculation, etc...)I learned a great deal from the uber-smart data scientists on my team and they in turn, picked up a nugget or two from me. We had fun solving not only the modeling challenges, but the attendant data prep challenges as well, coming up with novel, interesting, and simple-to-complex ways to deal with sparse or missing data (or nonconforming data).All of our efforts were eventually aimed at optimizing something: generally that was forecast and predictive accuracy to empower the business/organization-as-a-whole to increase its margins to become more profitable and effective.

Marana, Arizona, Us

For five years I served as the Chief Improvement Officer for a large suburban school district in the Tucson area. I was asked to serve in this capacity after leading the district through several improvement initiatives, including those focused on technology, instruction, and curriculum.As part of his role, I led research, curriculum, instruction, assessment, technology, instructional technology, and evaluation across the entire organization of 1600 employees and 13,000 students in 17 school sites.I was instrumental in leading a dedicated and highly skilled team within his office (they are actually the ones who deserve credit) in the following efforts:*Complete Transition to Common Core Standards*Adoption and Implementation of the Gradual Release of Responsibility Instructional Framework*All standardized and performance-based testing initiatives, including AZ Merit*Adoption of an asynchronous Learning Management System (LMS)*Adoption and implementation of a Data Warehouse and Analytics and Reporting Solution via Versifit Technologies*Complete re-structuring of Professional Learning and all of the attendant systems to support it (from needs assessment to delivery to technology)I left MUSD to return to my passion of deeply intellectual work in the private sector by way of data science.

Marana, Arizona, Us

In Dr. Kramer's first five years back in public education, he was hired to lead the organization to a more evidence-based approach to solution-forming and problem solving. Publishing multiple fact sheets and research briefs, Dr. Kramer's initial efforts focused on educating leaders and staff to consult the evidence base more frequently.Dr. Kramer also was responsible for implementing a new student information system, the districts' primary mission-critical IT system. As part of this effort, he led MUSD to adopt an online gradebook and parent/student portal. With monumental effort and leadership from district administrators, school leaders, and teacher-champions, the transition to Synergy was largely successful and well-received (although not perfect, as no new SIS adoption is!).Finally and in his last two years, Dr. Kramer worked hard to systematize the core concepts from John Hattie's meta analysis work (Visible Learning) to inform multiple change efforts underway in the district. Relying on evidence to drive change was, and remains, the central focus of improvement efforts in MUSD.

I staffed and managed the company's largest account, representing 70% of its revenue stream. I also developed in Hyperion Designer as well as Java Script. 1Answer was a Hyperion partner and we did most of our work in the BI space with their product(s).

Doctor Of Philosophy (Phd), Program Evaluation And Statistics

Master Of Science (M.S.), Agricultural Education