Human Resources Research Organization (HumRRO)

We are seeking individuals with a profile of skills in psychometrics, statistical computing & programming, simulation-based research, natural language processing, and machine learning.. Dual degrees/certification or relevant experience as an alternative to a degree/certification in (a) Computer Science, Mathematics, Statistics, or related fields and (b) Industrial-Organizational Psychology, Educational Measurement, Psychometrics, or related fields.. A minimum of 3-5 years of relevant experience; a Bachelor's, Master's, or PhD degree in Computer Science, Mathematics, Statistics, or related fields and a Master's, or PhD degree in Industrial-Organizational Psychology, Educational Measurement, or related fields.. Experience with modern analytic tools, frameworks, systems, and infrastructures (cloud computing, AWS, scalable HPC, virtual machines, dockers, Hadoop, Spark).. Experience with deep learning frameworks such as Keras, Tensorflow, Pytorch, etc.

machine learning

Are you interested in using innovative data science to help make decisions in high-stakes assessment settings affecting individual employees, students, members of the military, and credentialed professionals?
The Human Resources Research Organization (HumRRO), a non-profit national leader in workforce assessment, human capital consulting, and educational research, is seeking a full-time Data Scientist to join our growing organization. At HumRRO, you will be working with world-class scientific and practitioner staff to use data to help make challenging people decisions affecting government, military, education, credentialing, and private sector clients. As a non-profit, HumRRO is dedicated to work that contributes to science and society.
HumRRO research staff are predominantly organizational psychologists, educational measurement specialists, and statisticians. We also have a small but capable software engineering team. Increasingly, we find ourselves conducting data analyses of rising complexity involving traditional statistical methods alongside techniques related to machine learning. HumRRO is known for conducting analyses that meet the highest ethical and professional standards (e.g., Standards for Educational and Psychological Testing) while exploring the cutting edge. To that end, we seek qualified data science candidates interested in applying their skills to organizational and educational assessment challenges. We are seeking individuals with a profile of skills in psychometrics, statistical computing & programming, simulation-based research, natural language processing, and machine learning.
Note that we expect candidates to have demonstrated experience in relevant areas. The successful candidate will work among a team of researchers and conduct one or more of the following tasks:
Conduct quantitative data analysis using a variety of datasets, including retrieval, wrangling, processing, fusion, analysis, and visualization.
Use statistical modeling techniques to identify complex data patterns useful for predicting meaningful outcomes for employees, employers, organizations, and students.
Increase the efficiency and effectiveness of analytic processes, including automating processes where helpful.
Conduct simulations to inform the design, development, and evaluation of human capital and education-related decision-making systems.
Optimize existing code for improvement areas and ensure accuracy (e.g., increasing efficiency, reducing error).
Basic Qualifications:
Dual degrees/certification or relevant experience as an alternative to a degree/certification in (a) Computer Science, Mathematics, Statistics, or related fields and (b) Industrial-Organizational Psychology, Educational Measurement, Psychometrics, or related fields.
Hands-on programming for data analytics using R.
Ability to work closely with domain experts to develop tools/algorithms needed to answer research questions.
Solid communication skills (ability to explain tools and algorithms to a non-technical audience).
Interest in attacking applied problems related to measuring human capabilities in the workforce and educational domains.
Proven ability to work independently to learn emerging technologies, techniques, processes, languages, platforms, and systems.
Strong analytic, critical thinking, and creative problem-solving skills.
Ability to work both independently and in a team.
US Citizenship is necessary due to contract requirements.
Preferred Qualifications:
A minimum of 3-5 years of relevant experience; a Bachelor's, Master's, or PhD degree in Computer Science, Mathematics, Statistics, or related fields and a Master's, or PhD degree in Industrial-Organizational Psychology, Educational Measurement, or related fields.
Experience With:
Advanced statistical analysis, e.g., supervised and unsupervised learning models and algorithms, and good basic data wrangling skills.
NLP tools, e.g., NLTK, spaCy, use of transformer models (BERT, GPT).
Program documentation and version control.
Database programming.
Interacting with internal and external (non-data science) clients to recommend appropriate analytic processes and tools.
Bonus Selection Factors:
Experience with modern analytic tools, frameworks, systems, and infrastructures (cloud computing, AWS, scalable HPC, virtual machines, dockers, Hadoop, Spark).
Experience with software development across lifecycles, including developing and maintaining production quality code.
Experience with deep learning frameworks such as Keras, Tensorflow, Pytorch, etc.
Applying deep learning frameworks to challenges in social and behavioral science domains.
Interpretability of ML models, particularly related to fairness and transparency issues.
All qualified applications will be considered regardless of race, color, religion, sex, national origin, age, marital status, sexual orientation, gender, gender identity, veteran status, medical condition, or disability. EEO/AA Employer/Vet/Disabled.
Named one of "50 Great Places to Work" by Washingtonian magazine, 2019, and one of the "Top Workplaces" by The Washington Post for 2020 and 2021.<br/><br/>#J-18808-Ljbffr

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