I employ advanced statistical methodologies to ensure the alignment of learning and educational platforms with fundamental principles of learning science and human learning and memory. Leveraging over a decade of statistical and research experience, I seamlessly engage with diverse datasets of varying scales and types (e.g., real-time clickstream, app/web-based, survey, and institutional data) on various platforms and software tools, such as R, Python, Spark, Snowflake, and Databricks, which enables me to use the most appropriate combination of tools to extract the best insights, then craft research-based, innovative solutions from the most intricate data landscapes. This role is a continuation of the previous where I am the expert quantitative researcher who conducts research and analyses to assess the effectiveness and impact of Pearson’s educational products, services, and other initiatives. I also lead, mentor, and support other team members specifically with data cleaning/wrangling, data quality and governance, best practices for visualizations, analyses, and methodology, and practical implementation of models.

I leverage advanced research design, statistics, and machine learning algorithms to create feasible, data-driven solutions to conquer everyday challenges and make a positive impact on the efficacy of Pearson products today, paving better, more strategic procedures for products to come. I specialize in working on higher education products and, even more specifically, products for STEM and math students. Some of my highlighted work includes fully automating data prep, analysis, and presentation for the Employee Pulse Survey and building a customer-centric, automated profile analysis that was based on effective/ineffective learning and used to target marketing and retention efforts.

As a published researcher and expert statistician, I seek new and exciting challenges via freelance opportunities to diversify my statistical and coding palette. My skills include cleaning and manipulating messy data, building appropriate models to answer questions, and leveraging clever visualizations to display complex information in an accessible manner. I have worked with large clickstream datasets, small and large surveys, electrophysiological data, and more to answer everything from specific to exploratory hypotheses. I can support you at every level of your project from advice to deployment and instrumentation to instruction/presentation and turn your project or data challenges into insights.I also provide resume writing/revamping, cover letter editing, and other job or school application materials. I am specifically skilled at helping individuals make the jump from academia to industry, tech-related jobs, and graduate school applications.

I build data pipelines that feed into R Shiny dashboards using sensitive, exploratory data for sleep studies, conduct statistical analyses, and consult on the research designs necessary to answer hypotheses accurately.

I consulted on an R course and taught students to use perform statistical analyses in R for a master's I/O psychology course and prepare them for industry and applied positions.

I taught an 'upper-division' broadcast course called Brain & Behavior. In this course, students learn about the connections between the brain, sensation and perception, cognition, and disorders of various systems.

• Increased the number of finished projects per month by 200% by establishing the project in-take process and a set of standards, hiring and training a mixed team of statisticians (qualitative, quantitative,and reporting) and data scientists and implementing Agile workflow (Jira).• Managed and scoped over 30 data science research projects from natural language processing to retention models. Analyses inform strategic and tactical decision making for teams across the college.• Reviewed work of other researchers for completeness, accuracy, and trustworthiness. Provide technical feedback on model selection, interpretation, and implementation.• Serves as liaison and consultant while collaborating closely with stakeholders to define and design research projects in a feasible and attainable method.• Built statistical models (logistic regression) to analyze the effectiveness of multiple programs. Have wrangled and implemented matching function for over a million observations of student-leveldata and used results pinpoint ways to increase student retention by over 10%.• Designs, implements, and analyzes survey data via Qualtrics and for campus-wide projects, presentations, and convocation.• Reinstated and oversaw the Institutional Review Board to ensure the College met federal ethical research standards.

• Inform policies that increase protective factors and reduce risk for delinquency and youth substance use by creating and comparing risk profiles and reporting risk assessments to multi-stakeholder community coalitions• Evaluate dimensions of risk and protective factors (motives, culture, attitudes) using psychometrics and multi-level structural equation modeling on survey data collected from students, parents, and school administrators to inform school-level intervention strategies to reduce concussion non-disclosure • Presents data trends of concussion reporting to non-technical audiences using visualizations created in Tableau • Increased analysis efficiency by automating SPSS syntax files to generate reports and export to excel files of text responses• Collected and cleaned data from survey, school records, and other data sources.• Determined factors that systematically reduced substance use and juvenile delinquency to inform policies for a multi-stakeholder community coalition.

• Averaged 4.85/5 score for encouraging a creative and collaborative atmosphere where student ideas are heard and respected in lecture-based sciences courses with ~200 students per section• Led meetings for teaching assistants, other fellows, and “Let’s Talk Teaching Lunch” for graduate students interested in teaching• Facilitated student learning by managing a team of 4-6 graduate teaching assistants and 2-3 undergraduate teaching assistants through grading of written work, feedback, and test development• Improved the student learning platform by delivering information through active learning activities, formative assessment, and optimized PowerPoint lecture presentations • Involved in the development, implementation, and test runs of university-initiated programs to assist student’s in adapting to the university environment and teacher-specific expectations by increasing the quality and quantity of feedback received on academic work• Resolved questions regarding test development and research supported responses to student complaints by leading two Professional Development Workshops on the Science of Learning and Teacher-Student Interactions • Knowledgeable of campus-wide academic systems (Canvas, Blackboard, Banner, Desire2Learn)

• Delegating tasks and resourceful troubleshooting both in the lab and classroom.• Master’s thesis successfully pinpointed a predictive biomarker of psychosis from analysis of brain activity. • PhD Dissertation utilizes structural equation modeling to assess longitudinal exploratory interventions. • Mentored 30+ research assistants. 27% worked for 2+ years, 6 presented independent projects, 2 published at least 1 paper under my mentorship, and 3 are now in graduate programs.

- Presented interactive PowerPoint lecture on Multi-Level SEM to facilitate informed use of modeling techniques - Specialized in using Mplus to implement statistical analyses- Assisted in teaching the upper division SEM course offered at CSU to graduate students and faculty

I led an autonomous project with a research team to classify middle and high school Native American students into categories of substance use and determine how their patterns of use changed or remained stable over time: The model was based on a large epidemiology dataset (17,000+ observations) analyzed data in R and MPlus

• Encouraged interdepartmental collaboration by establishing a universal and compatible pipeline for analysis on a high-performance computing system (HPC) • Learned the FMRI data analysis program AFNI in 2 weeks.• Learned to code in Python using Ubuntu in the same timeframe.

• Improved diagnosis by creating genetic profiles of Rett Syndrome using a latent profile analysis • Added to the scientific community by producing an in-depth literature review for a published manuscript

• Administering assessments (RBANS, Trail making, mood evaluation) to participants with stages of dementia • Analyzed pre/post measures of neurocognitive abilities following attendance to symphonies.

• Created reports and data visualizations from multiple databases of student involvement in undergraduate conference per college and major for administrators, departments, deans, and colleges.

Project Title: A cross-sequential study of shifting social support as a stress mediator during major life transitions among young adult womenDescription:Significant life transitions can create an environment of shifts in supportive social relationships and risk factors. Marking these shifts may result in predictive information regarding establishment, confirmation and recalibration of self-identity as well as personal values and priorities. The first wave was presented at Eastern Psychological Association, the second wave of analysis was presented at the Association for Psychological Science (APS) in San Diego May, 2014. Other projects in M.E.A.L.S that I have led include: Mentors as Stress-Mediators for First Year College Students, Relationship between Self-Perception and Stress in First Semester College Freshmen, A Cross-Sectional Analysis of Independence in College Students, Parental Expectations and Influence on College Seniors, Relationships between high school size and transitional stress amongst first-year college women.

Courses include: 200-Level Statistics in Psychology and 300-Level Research Methods. Duties of the positions include: presentations, lecturer for 300 level course, APA format and research writing, proposal writing, tutor

An evaluation of the potential phototoxicity of CeO2 nanoparticles in retinal pigment epithelial cells in-vitro:• Analyzed nanoparticle data and spectral recordings of retina activity with various models include regression in SAS• Developed and executed molecular protocols for autonomous research project examining the potential phototoxicity of cerium dioxide (CeO2) engineered nanoparticles (EMNs) on human retinal epithelial (ARPE-19) cellsEffects of gestational ethanol inhalation on sensory function in rats:• Assembled the electroretinogram• Ran trials to examine the effect of exposure to ethanol-gasoline mixed vapors on prenatal rats• Assessed the developmental disturbances in the visual system using visual evoked potentials,• Coded and ran GLMS analyses in R and SAS• Presented findings at two research projects at national conferencesRelevant Training and Certification from EPA: • Cell culture with nanoparticles• Ethics in Animal-Based Research• Lab Safety Training (ISHEM)• Animal Facility Training: Barrier Training (ABC) • Pattern Reversal Visual Evoked Potential (VEP and Electroretinogram (ERG) system protocols and data analysis • Certified in Hands on Rat Handling and Wet Lab Basic Skills • Inhalation Anesthesia Systems in Rodents• Aseptic Technique for Rodent Survival Surgery• Data Analysis Programs: SPSSX, SigmaPlot, SAS• Biosafety: Bloodborne Pathogens

- Extract and create tables and figures for results section of a publication- Written reports of exploratory cluster analyses on spectrograms of bird vocalizations