Data/Analytics Engineer
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Requirements
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Clickhouse). • Strong analytical and problem-solving skills, with attention to detail. • Ability to communicate complex data concepts to both technical and non-technical stakeholders. • Experience with machine learning pipelines, MLOps, and feature engineering. • Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes). • Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform). • Background in building self-service data platforms for analytics and AI use cases. • Location & Remote • The position is based in our Paris HQ offices and we encourage going to the office as much as we can (at least 3 days per week) to create bonds and smooth communication. Our remote policy aims to provide flexibility, improve work-life balance and increase productivity. Each manager can decide the amount of days worked remotely based on autonomy and a specific context (e.g. more flexibility can occur during summer). In any case, employees are expected to maintain regular communication with their teams and be available during core working hours.
Responsibilities
• Develop and implement AI models to analyze large datasets for trends and patterns relevant to business decisions. • Collaborate with cross-functional teams to understand data needs and integrate insights into strategic planning. • Maintain a robust understanding of the company's products, services, markets, competitors, customers, industry regulations, etc., as they relate to our analytics work. • Design, develop, deploy, monitor, optimize, troubleshoot AI models and algorithms for data analysis tasks; ensure accuracy in results by validating model outputs with actual business outcomes when possible. • Stay current on emerging technologies relevant to the role (e.g., machine learning techniques) through continuous education or professional development activities such as workshops, conferences, webinars and/sabbatical leaves for research projects if applicable; share knowledge with team members by leading training sessions when appropriate. • Communicate effectively both verbally & in writing across various levels within the organization regarding data analysis findings that impact business decisions (e.g., presentations at alligator meetings). • Maintain confidentiality of sensitive information and comply with company policies on ethical use of AI tools; ensure proper documentation is kept for audit purposes where required by law or regulation regarding handling personal data under GDPR guidelines. ✅
Benefits
• 💰 Competitive salary and equity package • 🧑⚕️ Health insurance • 🚴 Transportation allowance • 🥎 Sport allowance • 🥕 Meal vouchers • 💰 Private pension plan • 🍼 Generous parental leave policy