Data Analyst
Department: Product \& Engineering
Location: Remote / Geneva
About the Role: As a Data Analyst at InvestGlass, you will be the driving force behind our data\-driven decision\-making processes. You will dive deep into large datasets generated by our CRM, marketing automation, and portfolio management modules to extract actionable insights. Your work will directly influence product development, sales strategies, and customer success initiatives. You will be responsible for creating comprehensive dashboards, generating regular performance reports, and identifying trends that can help our clients optimize their wealth management operations. This role is perfect for someone who loves turning raw data into compelling stories and strategic recommendations.
Key Responsibilities:
- Interpret complex data, analyze results using statistical techniques, and provide ongoing, comprehensive reports to internal stakeholders.
- Develop and implement data collection systems, data analytics strategies, and optimize statistical efficiency and quality.
- Acquire data from primary or secondary data sources, clean the data, and maintain our internal databases and data warehouses.
- Identify, analyze, and interpret trends or patterns in complex data sets to highlight opportunities for product improvement or business growth.
- Work closely with management to prioritize business and information needs, translating business questions into analytical queries.
Requirements:
- 1 to 3 years of proven working experience as a Data Analyst, Business Data Analyst, or in a similar analytical role.
- Strong knowledge of and experience with reporting packages (e.g., Tableau, PowerBI), databases (SQL), and programming (Python or R).
- Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS, etc.).
- Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Excellent communication skills, with the ability to present complex data findings in a clear and understandable manner to non\-technical audiences.
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