Job Closed
This listing is no longer active.
Everstake is a responsible validator trusted by 1M+ users across 85+ blockchain networks.
Head of Data Science
Location
United States
Posted
147 days ago
Salary
0
Seniority
Lead
Job Description
Head of Data Science
Everstake
• Own and evolve data science and analytics architecture across Everstake • Design and maintain scalable data pipelines, metrics layers, and analytical models • Lead technical decision-making across data platforms, BI, and orchestration • Translate blockchain, product, and business problems into clear data solutions • Define data standards, best practices, and development guidelines • Review code, data models, and pipelines for quality, performance, and correctness • Mentor senior data scientists and analysts, provide technical leadership • Partner closely with product, backend, infrastructure, and finance teams • Ensure data reliability, observability, and correctness in production • Actively contribute hands-on where technical depth is required
Job Requirements
- 6+ years of professional experience in data-related roles
- Strong experience as a Senior / Lead Data Scientist or Analytics Engineer
- Proven ability to lead technically strong teams and initiatives
- Ability to balance hands-on execution with leadership responsibilities
- Python — expert level (data processing, analytics, modeling, production code)
- Apache Airflow — 2–3+ years of hands-on experience (DAG design, dependencies, retries, backfills, monitoring, failure handling)
- Databases & Warehouses: ClickHouse, PostgreSQL, Snowflake
- BI & Analytics: Power BI and/or Tableau
- Strong understanding of semantic layers, metrics definitions, and data modeling
- Docker, Git, Grafana (monitoring data pipelines and platform health)
- Strong understanding of data modeling (facts, dimensions, slowly changing data)
- Experience designing KPIs and metrics that reflect business reality
- Strong SQL skills and performance-oriented thinking
- Practical experience in blockchain, crypto, or Web3 products
- Fluent English (B2+ or higher)
Benefits
- Opportunity to work on mission-critical Web3 infrastructure used globally
- Head-level role with real influence on data and technical strategy
- Fully remote work format
- Competitive compensation aligned with experience and seniority
- Professional growth in a top-tier Web3 engineering organization
- Strong engineering culture with focus on quality, ownership, and impact
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
Manager, Messaging Data Science – Engineering
NetflixDescribed as the world's top internet television network, Netflix is a publicly-traded entertainment company offering video-on-demand and streaming media. As an
• Lead a team of mixed technical roles (Data Scientists, Analytics Engineers, and Data Engineers) • Drive the vision and roadmap for the team • Be a strategic thought partner to shape the strategy of the broader Messaging domain • Drive a culture of innovation through collaboration with other leaders
• Lead and deliver the translation of complex biological and clinical questions into actionable analysis plans. • Architect and implement robust data pipelines that integrate large-scale genomic, phenotypic, laboratory, and real-world clinical datasets. • Conduct repeatable data analysis and modeling with a high degree of scientific and statistical rigor, for complex tasks such as understanding patient trajectories, elucidating variant effect, and identifying genotype-phenotype associations. • Write clean, maintainable, and well-documented code following best practices for version control, testing, and scalability. • Prepare technical reports, peer-reviewed publications, and conference presentations to share research outcomes with internal stakeholders and the broader scientific community. • Collaborate closely with both internal and external stakeholders to drive impactful research and development initiatives. • Ensure high standards of data privacy, security, and compliance are maintained in all projects.
Assistant Manager, CA Product Analytics – Optimization
Western UnionWe are passionate about honoring our employee's identity and fostering a feeling of belonging. Our commitment is to provide an inclusive culture that celebrates the unique backgrounds and perspectives of our global teams while reflecting the communities we serve. We do not discriminate based on race, color, national origin, religion, political affiliation, sex (including pregnancy), sexual orientation, gender identity, age, disability, marital status, or veteran status. The company will provide accommodation to applicants, including those with disabilities, during the recruitment process, following applicable laws.
• Drive product analytics, production quality management, and experience optimization for Canada’s digital experience. • Collaborate closely with regional product leadership and cross-functional teams. • Perform thorough production testing across the Canada experience. • Monitor error spikes in production, coordinate timely fixes, and safeguard customer experience stability. • Track funnel metrics to measure stability and identify conversion issues. • Partner with the Canada Regional Product Lead to generate funnel analytics and insights.
• Support markets with ENSUM+(Expert Net Sales Uplift Model) modelling for Expert-related financial planning. Develop and run ad-hoc investment choice simulations to inform local decisions. Empower markets with actionable insights. • Consolidate ENSUM+ & Expert MMM learnings from markets to inform central analyses and business-wide applications Identify Expert growth drivers and support prioritization across BMCs. • Conduct data quality audits and transform Expert-related datasets for use in MMM and other analytics. Enable reliable and accurate data for value tracking and decision-making. • Transition Expert tracking data to centralised systems. Support implementation of new analytics use-cases requiring data asset access and triangulation. • Lead end-to-end analysis triangulating Expert KPIs with market share/sales data. Deliver insights to support investor relations and executive decision-making. • Design and execute new test-and-learn experiments identified in the 2026-27 roadmap. Improve predictive models and business planning assumptions. Run validation of tools/models
