Senior Faculty Specialist

Senior Faculty Specialist (Data Scientist)

Organization's Summary Statement: University of Maryland's College of Education's Center for Educational Data Science and Innovation (EDSI) is dedicated to advancing research and practice at the intersection of data science, artificial intelligence (AI), and education. EDSI's mission encompasses three primary objectives: 1. Accelerating cutting-edge research that leverages data science and AI to address critical issues in education and advance education equity and effectiveness; 2. Bridging educators, researchers, policymakers, and industry leaders to promote evidence-based, ethical, and responsible use of data and AI in education; 3. Transforming education systems to achieve greater equity, efficiency, and effectiveness for all students through innovative technological advancements and policy solutions. Through these objectives, EDSI aims to position the University of Maryland College Park at the forefront of innovation in educational data science, policy analysis, and the application of AI in learning environments.

EDSI is seeking a highly skilled Senior Faculty Specialist (Data Scientist) to lead data-driven research initiatives aimed at improving educational practices. This position involves working with a diverse array of educational data types, coordinating research collaborations, supporting the integration of research insights into innovative educational products and interventions, and exploring cutting-edge technologies, including generative AI, to enhance educational research and practice. Major responsibilities will include overseeing the collection, management, and analysis of complex educational data from multiple sources, including classroom recordings, administrative datasets, and proprietary learning tools. Additionally, the Senior Faculty Specialist will translate research findings into actionable tools and products, working closely with software developers, educational partners, and researchers.

Minimum Qualifications: Education: Master's degree or higher in Computer Science, Data Science, Statistics, Education, or a related field. Experience: Demonstrated experience in managing large datasets and conducting advanced data analyses. Experience in project management and collaboration in a research or academic setting. Knowledge, Skills, and Abilities: Expertise in data analysis and machine learning, with experience applying these techniques. Strong programming skills in Python, R, or similar languages. Familiarity with experimental design and causal inference methodologies. Familiarity with or interest in applying generative AI techniques. Excellent communication skills, passion for educational research, and a desire to contribute to impactful educational research. Preferences: Recent PhD in relevant field. Expertise in data analysis and machine learning, with experience applying these techniques in an educational context preferred. Familiarity with experimental design and causal inference methodologies, particularly in educational contexts. Familiarity with or interest in applying generative AI techniques in educational contexts is a plus. Physical Demands: Sedentary work is performed in a normal office environment and requires the ability to operate standard office equipment and keyboards. Must be able to read computer screen and type for extended periods. Must have the ability to walk short distances, and/or drive a vehicle to deliver and pick up materials.

Required Job Application Materials: Resume/CV, Cover Letter, References

Best Consideration Date: January 31, 2025

Open Until Filled: Yes

EDUC-College of Education

Faculty Non-Regular (Fixed Term)

$85,000 - $105,000

Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.

The successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.

The University of Maryland, College Park is an Equal Opportunity/Affirmative Action Employer; all qualified applicants, including veterans and people with disabilities, will receive consideration for employment. UMD is actively engaged in recruiting, hiring, and promoting underrepresented communities. Please read the entire University of Maryland Equal Employment Opportunity and Affirmative Action Statement of Policy. Women, Minorities, Disabled, Veterans, and LGBTQ+ Welcome!

The University of Maryland, College Park, an equal opportunity/affirmative action employer, complies with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action; all qualified applicants will receive consideration for employment. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, religion, sex, national origin, physical or mental disability, protected veteran status, age, gender identity or expression, sexual orientation, creed, marital status, political affiliation, personal appearance, or on the basis of rights secured by the First Amendment, in all aspects of employment, educational programs and activities, and admissions.

The University of Maryland (UMD) does not discriminate on the basis of sex, gender identity or expression, sexual orientation, race, color religion, national origin, ethnicity, physical or mental disability, protected veteran status, age, genetic information or any other characteristic protected by law in its programs and activities. Specifically, Title IX prohibits discrimination on the basis of sex in UMD programs and activities, including with respect to admission and employment.