Job Description

Responsibilities

• Design, develop, and maintain interactive dashboards in Tableau to support both recurring and ad-hoc reporting needs across various growth functions and leadership teams, enabling real-time performance tracking and insights.
• Write and optimize complex SQL queries on Databricks to drive business growth in user acquisition, campaign ROI, and customer lifecycle management.
• Partner with cross-functional teams—including growth, product, data engineering, and external vendors—to improve data infrastructure, independently troubleshoot pipeline issues, and ensuring accurate, scalable, and efficient data pipelines that support business goals.
• Streamline and automate recurring data workflows and processes, manage SQL automation and job scheduling, and maintain thorough documentation to enhance team productivity and data reliability.
• Develop analytical models to inform marketing strategies, including predictive LTV, lead scoring or marketing mix modeling, providing actionable insights for campaign planning and optimization.
• Leverage statistical techniques and business intelligence tools to uncover trends, patterns, and opportunities that inform strategic growth decisions.
• Collaborate closely with cross-functional stakeholders to implement data-driven solutions and support end-to-end project delivery, ensuring alignment with business objectives and timelines.
• Stay proactive in professional development by exploring emerging AI tools and methodologies in data science and marketing analytics, continuously enhancing analytical capabilities and industry knowledge.

Requirements

• Bachelor's degree in a quantitative field such as Computer Science, Statistics, Engineering, Information Systems, or related fields.
• 2+ years of experience in data analysis or a related field. Experience in the Crypto and Technology industry is a plus.
• Proficiency in SQL, Databricks, and Tableau for processing, analyzing, and visualizing large datasets.
• Experience with statistical software (e.g., R, Python) and libraries for managing, manipulating, and analyzing data.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Adept at querying, report writing, and presenting findings.
• Understanding of digital marketing concepts, such as user acquisition (organic, non-organic, partnerships, etc.), campaign management, and customer lifecycle management.
• Familiarity with tools like AppsFlyer, Google Tag Manager, Google Analytics, and SensorTower.
• Strong communication skills to effectively convey complex data insights to non-technical stakeholders and to translate business needs into technical and data requirements.
• Ability to thrive in a fast-paced environment, manage multiple projects, and adapt to shifting priorities.