Head of Impact
| Company | Kiddom |
|---|---|
| Location | San Francisco, CA, USA, New York, NY, USA |
| Salary | $150000 – $250000 |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- 7+ years of relevant experience, preferably in applied research developing and evaluating educational technology products.
- Doctorate in developmental psychology, cognitive psychology, Educational Leadership, Research Methods, or a related technical field.
- Familiarity with data warehouse design, development, and best practices.
- Strong understanding of learning science as it applies to pK-12.
- Passion for education and a commitment to empowering educators and students through innovative solutions.
Responsibilities
- Increase overall product results, i.e. student growth and achievement on curricular programs and increased teacher confidence in using Kiddom’s products.
- Lead the design and execution of validation tests and studies for Kiddom products and programs to validate impact. Coordinate with stakeholders (internal and external) to carry out validation studies.
- Collaborate with Kiddom’s CEO and CAO, data scientists, engineers, instructional designers, product managers, and SMEs to develop and refine products and programs.
- Apply a mixed-methods expertise to take advantage of different qualitative and quantitative research methods, including when and how to apply them during the product development and validation process.
- Go directly into classrooms (with or without support) to support validation work and observe product utilization, behaviors, etc. and to support.
- Partner with Kiddom’s co-founders to offer guidance and leadership to colleagues in validation of educational technology products.
- Create detailed documentation of work results, including white papers, memos, and SOPs.
- Presents periodic tests and results to the CEO and CAO and other members of Kiddom leadership.
Preferred Qualifications
- Fluent in SQL and Python (or other scripting languages), comfortable with GIT (more important you know how to do good designs the data science team can help execute).
- Experience in applying both data-backed heuristics and machine-learning techniques to solve practical product problems.
- Experience with knowledge graphs, NLP, or topic modeling.