Data Analyst - Performance Marketing

About Midas Team

• We solve challenging problems and build 10x better products
• We expect hard work, high ownership, a strong desire to learn. 
• We bring the best people, holding high quality standards, and an environment of speed and ambition
• You will get to push your boundaries and learn from the best

What You’ll Do

• Data Analysis & Insight Generation: Analyze large datasets to deliver strategic recommendations to Performance Marketing team, including root cause analysis of key problem areas.
• Reporting & Dashboard Development: Build product performance dashboards with KPIs, prepare monthly and ad hoc reports, and manage automated reporting processes.
• Data Visualization & Storytelling: Create clear and impactful visualizations that effectively communicate insights and tell the story behind the data.
• Communication & Collaboration: Present insights across the organization through reports and presentations, while working closely with product and engineering teams to inform and support strategy.
• Data Infrastructure & Organizational Skills: Develop datamart and DWH structures for internal and self-service use, demonstrating strong organizational, detail orientation, and prioritization skills.
• Impact Creation & Ownership: Take end-to-end ownership of analyses and initiatives, ensuring that insights lead to actionable outcomes, measurable improvements, and meaningful business impact.

Cultural Competencies

• Takes full ownership — doesn’t wait, just solves
• Questions assumptions and rebuilds from first principles
• Balances speed and quality — ships fast, but always clean
• Collaborates fluidly across teams; communicates clearly, with empathy and precision

What You’ll Bring

• Bachelor’s or Master’s degree in Business Administration, Economics, Management Engineering, Industrial Engineering, or a related quantitative field.
• Strong proficiency in SQL, Tableau (or other data visualization tools); knowledge of Python is a plus.
• Design and analyze A/B tests, create predictive and explanatory models, and conduct proactive analytical projects to improve product performance.
• Knowledge of customer acquisition, re-engagement, and retention strategies to support product growth.
• Ability to handle complex projects and apply statistical methods (e.g., hypothesis testing, logistic regression) to measure results and drive insights.
• Identify and highlight opportunities for improvement across the user journey from a product funnel analysis perspective.