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Jobs/Data Analyst Role/Ledger - Data Analyst - Internship
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Ledger

Ledger - Data Analyst - Internship

Paris, France, Metropolitan - Hybrid5d ago
In OfficeInternEMEALife InsuranceInsuranceData AnalystData Science InternSQLPythonContent CreationTraining DevelopmentLearning & Development

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Requirements

• Education: Master’s degree student (M2) in Data Science, Data Engineering, or a related field. • Education: • Technical Skills: Strong proficiency in SQL and Python for statistical analysis and Machine Learning. • Python • Tools: Hands-on experience with dbt and Tableau is a significant advantage. • Tools: • Tableau • Soft Skills: Deep curiosity for Generative AI, high autonomy, and a pedagogical mindset to share knowledge across the company. • 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

• AI Enablement: Drive AI adoption by creating educational content on the Sana platform (tutorials, guides for AI Studio) and assisting non-technical teams in leveraging tools like Cursor or Google AI Studio. • AI Enablement: • Cursor • Google AI Studio • Analytics Engineering: Handle day-to-day data requests and strengthen data foundations by reducing technical debt in our core models. • Analytics Engineering: • Data Science Automation: Industrialize and scale our "causal impact" and "pre/post" analysis frameworks using Python to transform manual tasks into standardized processes. • Data Science Automation: • Python

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