• Served a principal developer in series of applications (few shot, RAG chat) leveraging AWS Bedrock LLMs designed to write task statements, extract KSAs, create competency models, and tailor competency models to job announcements retrieved from the USAJobs API. Created a set of LLM output evaluation metrics to help end users provide useful feedback for prompt engineering and fine tuning.• Conceived, promoted, and drove Tableau-based product concept that automatically generated visualizations of top featured insights from turnover risk model in a storypoint dashboard (based on original python code) and provided automatically updating description and practical recommendations using generative AI.• Built GitHub repository of R code embedded in Quarto Markdown (qmd) to automate the generation of a 6-chapter report as a Word document containing tables and visualizations.• Conducted data analysis in Python including a KMedoids cluster analysis to determine learner personas, and wrote the technical report. Presented post-onboarding career guides and social networking programs to encourage lateral growth, career pathing, and social cohesion among early tenure employees. • Led people analytics research for organizational network analysis using Microsoft’s Viva analytics Advanced Insights and MGDC data. Identified specific data needs from survey platforms, internal relational databases, and graph data from Microsoft in consultation with data engineers. Queried data from Azure using pyspark and analyzed data using python. Developed survey pruning protocol using both quantitative (item analysis) and qualitative (SME ratings) methods. • Program evaluation via needs assessment, SME interviews, Qualtrics surveys, & academic literature review. Constructed survey items to measure predictor (beliefs/attitudes/expectations) and outcome (learning/performance/motivation/satisfaction) constructs for pre & post surveys.

• Wrote a 4-part web-scraping script to generate a searchable database in Excel to save the time of staff who would otherwise have to manually navigate through slow online databases.• Built library in Python that allows users to retrieve up-to-date reports in proper format with single, easy-to-use functions.• Built Python scripts to automate data reporting from using multiple external files, email database retrieval and web scraping from online databases. I have many recent examples to share.• Linked data using granular data manipulation methods (e.g., iterative string matching via regular expressions) in Python, Pandas, and Excel, to link data based on irregularly spelled client names, timestamps, and ID numbers• Completed monthly reports containing visualizations of key performance metrics to identify performance gaps at various levels of workflow.• Cleaned, aggregated, filtered, and merged raw performance data from city-wide databases with large data sets exceeding 100,000 cases to compute risk assessment metrics using Python, Pandas, and Excel• Partnered with the senior leadership of various teams and agencies to improve data usage protocols involved in program evaluation, performance monitoring, risk-scoring, and Medicaid fraud detection• Built agency’s annual performance, strategy, & action-planning presentations in collaboration with 4 teams

• Validated 9 original assessments using multilevel CFA and used them to predict employee attitudes• Designed & tested a predictive model of performance based on performance feedback reactions using experimental procedures to manipulate performance feedback characteristics and measure performance motivation using a variety of behavioral measures (click count, time on page, with VBA Excel)• Tested conditional process models (e.g., mediated moderation) & parallel mediation using hierarchical linear regression with time series data in Mplus• Created original methods to validate and screen surveys based on survey time completion, timestamp proximity, attention- and comprehension-check measures leading to 50% increase in findings• Developed training materials for research assistants & participants leading to data collection from 1800+ subjects, 460 involved in 3-stage longitudinal design with up to 12 repeated measures over 12 to 90 days• Recruited, interviewed, and trained 10+ research assistants to use data collection software, screen research participants, admin a help-desk, export data from an external database to evaluate participant noncompliance, and administer participant training and testing• Established a predictive model of work-family balance determinants and provided evidence that although domain-specific job autonomy is the strongest predictor, non-work factors also contribute• Identified measurement issues in 70+ years of interpersonal conflict research that precluded the study of causal determinants; provided evidence for a predictive model linking daily workplace events to conflict perception and job satisfaction using time series data

• Built 100+ PowerPoint presentations on: job analysis, performance management, assessment, legal issues, employee development, employee selection, training transfer, engagement (see course list)• Conceived of and implemented “zero-textbook cost” courses on Psychology of Motivation and Employee Training and Development using academic research and applied publications (vs. a traditional textbook)• Coached hundreds of undergraduate and graduate students via in-person presentation feedback sessions• Constructed knowledge tests that consistently yielded a near-normal distribution (i.e., effectively discriminated between students at all competency levels)• Consistently achieved above average ratings from both student and faculty course evaluations• Led discussions on interpreting research findings skeptically and deriving practical implications for managers

• Conceived of & persuaded City Tech to implement a program evaluation of quantitative reasoning program• Persuaded stakeholders to transition from paper- to web-based surveys to reduce bias/data-entry errors• Conducted needs assessment via 8 SME interviews and an academic literature review• Constructed survey items to measure predictor (beliefs/attitudes/expectations) and outcome (learning/performance/motivation/satisfaction) constructs for pre & post surveys• Presented statistics, visualizations, and evidence-based recommendations via 3 technical reports

Dr. Marisa Silveri Lab• Study Recruitment: scheduling participants using Craigslist and Goggle Calendar• Study Coordination: scheduling research staff, explaining study procedures, obtaining assent and consent, administering questionnaires, collecting and testing urine samples• Data Management: coding, storage and analysis• Magnetic Resonance Safety Certification: required for working in MRI space

Dr. Daniel Gilbert Lab• Data Collection: Scheduling and running participants in two studies of social experience and memory using Sona Experiment Management System.• Data Entry: Using Microsoft Excel on Google Docs.• Certification: Completed Harvard Ethics Training in Human Research (HETHR).

Dr. Sam Sommers Lab• Data Collection: Scheduling and running participants in interaction study of racial anxiety.• Data Entry: Coding nonverbal and verbal expression data, and entering data using SPSS.• Library Research: Collecting articles on research methods from PsychARTICLES and Pubmed.• IRB Management: Organized filing system in preparation for IRB audit.

Dr. David DeSteno Lab• Data Entry: Coded nonverbal expression data using Noldus Observer XT. • Research Design: Participated in research planning, structure and implementation.• APS Conference 2010: Presented a poster on nonconscious imagery and trustworthiness.