Senior Data Scientist

Vibrant Emotional Health is seeking a Senior Data Scientist to join its remote team, applying data-driven insights to enhance program outcomes and operational effectiveness. This role centers on building, deploying, and maintaining models and analytical reports that support evidence-based decision making across programs and operations. The position covers the full data science lifecycle, from exploration and model development to deployment, monitoring, and stakeholder communication.

As a hands-on contributor, you will collaborate with data engineers and business partners to translate complex analyses into clear, actionable insights for program staff, leadership, and external partners. You will also help raise data literacy through training and workshops while maintaining robust infrastructure on AWS for model deployment and governance.

Responsibilities

• Architect and operationalize predictive models and analytics dashboards aligned with core business and program goals.
• Ensure transparency by making models and reports explainable, well-documented, and accompanied by explicit assumptions, opportunities, and limitations.
• Monitor deployed models for data drift, performance degradation, and data quality issues; lead remediation efforts as needed.
• Translate complex analytical findings into accessible insights for program staff, leadership, and external partners.
• Promote data literacy across the organization by partnering with business users to illustrate how models inform Vibrant's work.
• Develop and deliver training materials and workshops on data literacy, analytical thinking, and model interpretation.
• Collaborate with data engineers and analytics teams to ensure data pipelines and infrastructure support modeling and reporting needs.
• Apply statistical and machine learning methods with rigor, selecting appropriate techniques, validating assumptions, and assessing uncertainty.
• Contribute to Vibrant's data science infrastructure, including model registries, version control, and deployment pipelines on AWS.
• Support ad hoc analytical requests from program and operations teams.
• Additional duties as assigned.

Requirements

• Strong proficiency in Python and/or R for data analysis, modeling, and reporting; familiarity with libraries such as scikit-learn, pandas, and tidyverse.
• Experience with developing, validating, deploying, and maintaining models and ongoing quality control in production environments.
• Hands-on experience with AWS data science services, including SageMaker for model training and deployment.
• Advanced statistical knowledge covering regression, classification, clustering, causal inference, and experimental design.
• Experience working with large, complex datasets in cloud-based data warehouses (Redshift, Snowflake, or similar).
• Excellent written and verbal communication skills; ability to present findings clearly to technical and non-technical audiences.
• Strong analytical curiosity, attention to detail, and the ability to work independently on ambiguous problems.
• High level of influencing ability.
• Bachelor’s or Master’s degree in a quantitative discipline; minimum 4 years of relevant experience.

Technologies

• Python
• R
• scikit-learn
• pandas
• tidyverse
• SageMaker
• AWS
• Redshift
• Snowflake

Compensation

USD 99,800 - 132,300 per year

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Supplemental income insurance
• Employer-paid disability insurance
• Employer-paid life insurance
• Pre-tax FSA for medical and dependent care
• 401(k) available

Physical Requirements

• Must be able to remain in a stationary position 50% of the time.
• Regularly operate a computer and other office equipment.
• Frequent video calls with internal and external stakeholders.