The TMW Center is looking to solve the problem of assessing the quality of early language environments for young children, and to develop evidence-based interventions to promote cognitive and social-emotional development, with a focus on children living in poverty.
Requirements
- Knowledge and skills developed through 2-5 years of work experience in a related job discipline.
- Prior experience setting up data labeling and validation processes.
- Demonstrated understanding of data science management, Machine Learning and Data operations.
- Experience building out ML operations teams and processes.
- Experience with statistical modeling and programming.
- Advanced Degree in economics, data science, data analytics, computer science, software engineering or related fields strongly preferred.
- Knowledge and skills developed through 5 years of work experience in a related job discipline, strongly preferred.
Responsibilities
- Lead data labeling effort to build ground-truth corpus for existing and future algorithms, including identifying data requirements and protocols.
- Determine validation criteria and metrics across models and settings/partnerships/use cases.
- Collaborate with data management teams, and application development teams to identify and capture the data necessary to perform validation.
- Recruit, train, and lead a team of data labelers.
- Ensure alignment between the validation roadmap and Center’s priorities.
- Establish timelines and strategies for the validation of different algorithms.
- Work with ML and engineering teams to develop and manage pipelines for continuous algorithm validation and optimization.
Other
- Minimum requirements include a college or university degree in related field.
- 2 years of experience managing people, strongly preferred.
- Excellent strategic planning and execution skills.
- Strong problem-solving skills.
- Ability to balance short-term, long-term, and big picture objectives.
- Resume (required)
