Daniel Martin Email & Phone Number

Los Angeles, Ca, Us

Claremont, California, United States

Responsible for overseeing the construction of the S&P/Drucker Institute’s Corporate Effectiveness Index Scores and Rankings.Responsible for communicating technical aspects of the index construction process and the factors underlying a company’s ranking to various stakeholder groups.Responsible for communicating strategic implications of a company’s ranking to various stakeholder groups.

Claremont, California, United States

• Responsible for building a repository of R and Python code to build the S&P/Drucker Institute’s Corporate Effectiveness Index, which ranks companies in terms of 5 dimensions of corporate effectiveness and is published annually in the Wall Street Journal. In doing so, my responsibilities included…o Distinguishing between primary data and calculated data based on a repository of historical index data.o Identify mapping processes used to transform primary data into calculated data.o Identify mapping processes used to transform calculated data into the 5 dimension scores.o Identify mapping processes used to transform calculated data into the institute’s overall effectiveness score.o Construct syntax-based methods of re-creating the Index rankings in both R and Python in order to automate the construction of the index rankings in future years• Project information can be found at: https://drucker.institute/programs/sp-drucker-institute-corporate-effectiveness-index/

Participation in efforts aimed at developing predictive models of health risk and patient outcomes, with responsibilities including:- Defining prediction tasks and target variables- Data Cleaning - Feature engineering - Feature selection - Training & Evaluation of Machine Learning Models for Unsupervised & Supervised Classification tasks, Regression-based Cost and Risk prediction tasks, &Natural Language processing.

Teaching graduate level statistics and computer programming related to the use of quantitative methods for research in psychology and related fields in the behavioral sciencesResponsibilities include: Preparing assignment materials, grading assignments, hosting weekly office hours to review course material, assisting course professor in preparing and conducting weekly lectures.Courses Taught:Multilevel Modeling (MLM)• Topics covered include: R for statistical programming, Theoretical foundations of MLM and clustered data analysis, Clustered variance decomposition and cross-level interactions in MLM, MLM for longitudinal data analysis, Generalized and Multivariate MLM, Cross-classified and Multiple Membership modeling, Specialized Estimation techniques including Bayesian & Multilevel Structural Equation Modeling.Structural Equation Modeling (SEM)• Topics covered include: R for statistical programming, Path Analysis, Theoretical foundations of SEM, Mediation & Moderation in structural models, Multilevel SEM.Factor Analysis • Topics covered include: R for statistical programming, Theoretical foundations of factor analysis, Principal Components Analysis, Exploratory Factor Analysis, Confirmatory Factor Analysis, Robust Bifactor and Higher order factor models, Multigroup Confirmatory Factor Analysis, Factor analytic techniques for assessing internal consistency reliability in measurement scales.

Principal Consultant on Quantitative Research Methodologies for the Leadership and Organizational Vitality (LOV) Lab at Claremont Graduate University Responsible for leading quantitative research efforts on projects involving the application of positive psychological science in organizational settings.Projects have included:1) Statistical Validation of scales designed to measure worker vitality and well-being. Validation procedures involved:- Exploratory Factor Analysis (EFA)- Confirmatory Factor Analysis (CFA)- Assessment of Internal Consistency & Composite Reliability Metrics - Multi-Group CFA for Measurement Invariance Testing with respect to measurement occasions and level of leadership position held by study participants - Structural Equation Modeling (SEM)- Specification of Multi-Stage Mediation Models- Specification of Cross-Lagged Panel Models2) Development and Evaluation of Machine Learning models to predict various wellness metrics from self-assessments of 24 character strengths defined by the Virtues In Action (VIA) Institute. Involved Cross-validated training, hyper-parameter tuning, and out-of-bag testing of various models, including…- Multiple Linear Regression- Elastic-Net Regression- Gradient Boosted Tree Regression- Random Forests Regression

Principal Consultant and Operations Coordinator for the Claremont Graduate University Accenture Talent Innovation Lab. As Operations Coordinator I share recruitment, budget tracking, project and budget proposal drafting, and project staffing responsibilities amongst members of the lab leadership committee. As a Principal Consultant I share responsibility for contributing to and managing projects contracted to the lab by Accenture’s responsible assessments team. In this role I’ve lead projects related to the construction of Behaviorally Anchored Rating Scales (BARS), where my responsibilities have included:• Coordinating communication between internal teams and clients• Overseeing interview scheduling.• Overseeing the development of qualitative coding schemes employed in the extraction of critical incident statements from interview transcripts. • Constructing methods and procedures for the quantitative validation of critical incident statements• Development of data cleaning and wrangling algorithms deployed on multiple survey datasets comprising up to 60,000 data points in Python and R. • Constructing proprietary metrics used in the automation of BARS scoring.• Employing Monte Carlo Simulations in Python to psychometrically validate automated BARS scoring metrics and test their robustness to variation in the underlying item structure of BARS.

Research Associate with the CGU Accenture Talent Innovation LabIn this role I have carried out a variety of analytic tasks on survey data including:o Data wrangling and cleaning on app. 40,000 data points from 9000 respondents in R.o Conducting Chi-Square Analyses on categorical response data in R.o Conducting Non-Parametric Analyses on numerical response data in R.

Member of Prodoscore’s Behavioral Science Research Team:In this role I have worked on a variety of tasks related to data analytics including:• Constructing labeled training data for BERT language models used in Sentiment Analysis.• Data Preparation, including both data cleaning and data wrangling on large datasets consisting of upwards of 500,000 data points comprising both longitudinal and cross-sectional components in Python and R• Social Network Analysis including:o Constructing graphical and matrix representations of communication network data in R and Python.o Constructing Monte Carlo simulations to assess the statistical properties of proprietary network connectivity metrics in Python• Working with time series data including: o Leveraging variable lag autocorrelation functions to assess changes in dependence of data points across varying time horizons in R.o Leveraging Fourier transforms to assess seasonality effects in R.• Conducting mixed-effects multilevel regression analyses in R to account for dependence of longitudinal data nested within individuals.• Constructing proprietary ensemble-stacking models to predict employee attrition, including all necessary cross-validation and testing.

Burbank, California, United States

• Teaching undergraduate junior and senior-level statistics for psychology and related fields in the behavioral sciences • Course Number Psyc 331: Advanced Statistics for the Behavioral Sciences• Topics covered include: Theoretical Foundations of Null Significance Hypothesis Testing, Z-tests, Single Sample T-Tests, Independent Samples T-Tests, Related Samples T-Tests, One Way Between-Persons ANOVA, One Way Within-Persons ANOVA, Two Way Between-Persons ANOVA, Correlation, Linear Regression, Multiple Regression, Mediation, Moderation, Non-Parametric Analyses.

In this role I’ve carried out a number of analytic tasks on survey data including:.• Data Wrangling and cleaning on app. 12,000 data points from 300 respondents in R.• Development of Likert response items. • Exploratory and Confirmatory Factor Analysis of Likert response items in R as part of scale validation studies.• Leveraging K-means and Hierarchical Clustering algorithms to organize qualitative data for thematic analysis of free response items in Python.• Constructing graphical and matrix representations of communication network data in Python.• Extracting network-level density and transitivity metrics from network data in Python. In this role I’ve also contributed to the construction of evidence-based exercises used in a variety of leadership and professional development workshop series.

Santa Monica, California

Santa Monica, California

Doctor Of Philosophy - Phd, Positive Organizational Psychology

Bachelor Of Arts - Ba, Psychology

Bachelor Of Science - Bs, Accounting

Associate Of Science (A.S.), Business Administration And Management, General

Associate Of Science (A.S.), Accounting