Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Construct and enhance Humin's data and measurement framework, which encompasses event taxonomies, schemas, data quality assessments, and analytical infrastructure.

• Convert Product and Science requirements into specifications for instrumentation, acceptance criteria, and validation tests for the Engineering team.

• Oversee instrumentation and data quality, identifying tracking gaps, duplicate events, schema drift, and data inconsistencies, while facilitating remediation efforts.

• Create and sustain dashboards and reporting systems.

• Examine user behavior and product performance across various stages such as acquisition, activation, engagement, retention, churn, and wellbeing outcomes.

• Establish and validate effective engagement metrics, including the North Star metric, and correlate usage patterns with validated wellbeing outcomes.

• Utilize funnel, cohort, retention, and segmentation analysis, progressing towards survival analysis and predictive modeling.

• Assist in experiment design and analysis, evaluating the connections between product usage and validated wellbeing metrics.

• Convert product data into insights and recommendations that inform product strategy, personalization, and user experience.

• Carry out marketing, acquisition, audience, pipeline, and funder trend analyses.

• Develop reports for organizational KPIs and generate outcome metrics for grant reports and funder deliverables.

• Deliver clear, actionable analysis to leadership, the board, development, marketing, and other non-technical stakeholders.

• Aid in measurement selection, sample size planning, analysis, and interpretation in collaboration with the Science team.

• Implement psychometric principles to rigorously assess and interpret wellbeing outcomes.

• Transform statistical findings into easily understandable narratives.

• Contribute analyses to research publications, presentations, and technical reports.

⛳️ Requirements

• 2 to 4 years of experience in data science, product analytics, or a similar analytical role, or equivalent graduate research experience.

• Practical experience working with event or product data, including collaboration with Engineering on instrumentation and data quality.

• Experience in product analytics and applied statistics, incorporating funnel, cohort, retention, and related methodologies to understand user behavior and outcomes.

• Proficient in SQL.

• Skilled in Python or R.

• Experience with data pipelines and resolving data quality issues.

• Capability to translate stakeholder inquiries into precise data requirements and effectively communicate findings to non-technical audiences.

• Strong interest and dedication to, or lived experience with, wellbeing, mindfulness, and the science of human flourishing.

• Eligibility to work in the US without requiring sponsorship.

• Willingness to travel occasionally for staff gatherings and other organizational meetings and events.

• Background check required as part of pre-employment screening.

• Preferred: Experience in designing or analyzing experiments, including A/B tests, or familiarity with causal inference or quasi-experimental methods.

• Preferred: Knowledge of measurement design and psychometric concepts, including validated instruments and interpreting meaningful change.

• Preferred: Experience in applying predictive modeling or survival analysis.

• Preferred: Background in behavioral health, wellbeing science, or another research-informed product environment.

• Preferred: Experience in marketing, mobile, or business/revenue analytics.

• Preferred: Experience with mobile SDK instrumentation or reconciling and migrating legacy data.

• Preferred: Experience in a nonprofit or dual-revenue organization.

• Awareness of and commitment to diversity, equity, and inclusion principles.

🏝️ Benefits

• Comprehensive health and benefits package.

• Generous paid time off.

• Flexible/remote work arrangements.

• Professional development resources.

• Organization-wide forums and professional development opportunities.

• Opportunities to contribute to research publications.