Ledger - Products Analytics Engineer - Internship
Requirements
• Final-year student in Engineering, Computer Science, Data Science, or a related technical field seeking an end-of-studies internship. • Strong proficiency in SQL, Python scripting, and data modeling concepts. • Analytics engineering mindset with a focus on data quality, reliability, reproducibility, and documentation. • Understanding of A/B testing methodologies, statistical analysis, and funnel evaluation. • Familiarity with Product Analytics tools (e.g., Mixpanel, Amplitude) and data visualization tools is a strong plus • Hands-on experience or deep curiosity regarding AI agents and workflow automation is a strong plus. • Excellent written and verbal communication skills in English. • Interest in Web3, digital assets, and crypto is a plus. • At Ledger, we are dedicated to continually investing in our employees which is why we offer more than just salaries; we provide comprehensive compensation packages that include a wide range of benefits. Here are some of the benefits you can look forward to: • Flexible work options - Our hybrid policy allows employees to work from home up to 3 times per week • Flexible work options - • Health & Wellness support - Health and Life Insurance. • Health & Wellness support - • Financial growth opportunities - Employees can become shareholders in Ledger as well as other financial benefits depending on your country of work. • Financial growth opportunities - • Commuter allowance - Ledger offers a commuter allowance to contribute to your preferred means of transportation. • Commuter allowance - • Learning & Development - A comprehensive suite of training solutions providing a personalised learning experience for every employee. • Learning & Development • For regionally specific benefits, your Talent Acquisition contact will be able to provide you with more information.We’re committed to building an inclusive hiring process. If you need any adjustments or accommodations, just let us know, we’ll do our best to support you.
Responsibilities
• Cross-Functional Collaboration: Work closely with Product Managers, Data Engineers, and Data Scientists to deliver insights and support Growth/CRM personalization pipelines. • Cross-Functional Collaboration: • Experimentation & A/B Testing: Specify and support A/B test setups, funnel evaluation, and advanced statistical analysis for product features. • Experimentation & A/B Testing: • AI Governance & Automation: Help establish governance, guardrails, and custom skills for users querying analytics platforms (Mixpanel, Snowflake MCP) via AI tools, and contribute to building end-to-end AI-assisted tracking workflows. • AI Governance & Automation: • Tracking Quality & Investigations: Triage, investigate, and follow up on tracking issues to maintain data sanity. • Tracking Quality & Investigations: • Documentation & Enablement: Develop comprehensive documentation and data models (dbt/data mart) to empower stakeholders • Documentation & Enablement:
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