Overview
The Data Analyst will play a pivotal role in the organization’s data-centric environment, acting as the bridge between raw data and actionable insights. You will be responsible for collecting, processing, and performing statistical analyses on large datasets to help our marketing teams and the organization make informed decisions. You will create visualizations, generate reports, and provide insights from trends and patterns.How you'll make an impact
- Data Collection and Extraction: Gather data from diverse sources, stored in databases or coming from various parts of the organization. Use SQL to pull relevant data or build queries to generate specific datasets for analyses.
- Data Cleaning and Preprocessing: Work on data cleaning, handling missing values, and correcting inconsistencies to ensure the dataset’s accuracy and reliability.
- Data Analysis: Use data analysis techniques to test hypotheses, identify patterns, and establish correlations between variables, making findings relevant and precise.
- Visualization and Reporting: Transform raw data into visual formats such as charts, graphs, and dashboards using tools like Power BI. Ensure visuals make data easier to interpret and facilitate data-driven decision-making across marketing teams.
- Presenting Insights and Recommendations: Communicate insights in a clear, concise manner, presenting reports to stakeholders and decision-makers. Help bridge the gap between data findings and strategic actions.
About you
- Bachelor’s degree in marketing, business, finance, economics, computer science, or a related field.
- Three to Five years’ experience in a Data Analyst or a related role, with a track record of successful statistical analysis and data visualization.
- Excellent communication and interpersonal skills to collaborate with people across the global.
- Results-driven mindset with a focus on achieving marketing and business objectives.
- Familiarity with current marketing trends, emerging technologies, and industry best practices.
- Proactive, creative thinking and the ability to innovate marketing processes and strategies.
- Insurance experience is a plus.
Qualifications:
- Proficiency in SQL: Create complex queries, manipulate datasets, and perform database management tasks.
- Excel for Data Manipulation and Analysis: Data manipulation, data cleaning, and quick data analysis tasks, using built-in functions and pivot tables for summary statistics.
- Data Visualization Tools (Power BI, Tableau): Enable non-technical stakeholders to understand insights. Use Power BI to create interactive and visually appealing dashboards, making data insights accessible and understandable.
- Foundation in Statistics and Data Cleaning: Basic statistical knowledge. Apply statistical techniques to identify trends, perform data cleaning, and handle outliers, ensuring the quality and reliability of data analysis.
- Scripting Knowledge (Python or R): Preferred. Advanced data manipulation, automation of tasks, and integrating complex statistical models into data analysis workflows.
