Data Analyst
vor 1 Woche
About the Role
We are seeking a highly skilled Data Analyst to join our Business Analytics team at MOIA Operations Germany GmbH. As a key member of our team, you will be responsible for analyzing transactional data to identify trends and patterns in customer behavior, sales performance, and product performance.
Key Responsibilities
- Analyze large datasets to identify insights and trends
- Develop and maintain data visualizations and reports to communicate findings to stakeholders
- Collaborate with cross-functional teams to drive data-driven decision making
- Quantify the impact of product activities along the customer journey
- Evaluate the impact of changes in our product and proactively make suggestions to improve our product
- Automate recurring analytical tasks
- Define KPIs and implement them in our business reporting
Requirements
- Relevant work experience in analytics, business intelligence, or as an analytical consultant
- Strong communication skills and ability to connect and collaborate with diverse stakeholders
- Result-oriented working style to create analytical insights that have an impact for the business
- Proficiency in a language like Python/R and SQL
- Experience with business intelligence tools and cloud platforms is a plus
What We Offer
- Competitive salary and bonus
- Hybrid work setup with flexible working hours
- Budget and monthly expense allowance for home office setup
- Possibility of remote work from outside of Germany for up to 4 weeks per year
- Public transport ticket for commuting and traveling throughout Germany
- Subsidized fitness club membership or bike leasing
- Learning environment with continuous learning days and trainings
About MOIA
MOIA Operations Germany GmbH is a member of and is dedicated to actively fostering a workplace that celebrates and promotes diversity in various aspects such as age, gender identity, race, sexual orientation, physical or cognitive ability, and ethnicity. We are committed to creating a culture where people are accepted, respected, valued, appreciated, and included.
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