Data Analyst

Are you an experienced Data Analyst with experience in the Insurance sector?

We are currently looking for an experience data analyst with experience in the Insurance Industry. As a Data Analyst at thewave you will work on interpreting data, analyzing results, and providing insights to aid decision-making for our clients within the Insurance Sector. They typically work with large volumes of data, often using statistical techniques and software tools to uncover trends, patterns, and correlations. Our Data Analysts are instrumental in helping our clients understand their data, identify opportunities, and solve problems.

Overall, our Data Consultants play a crucial role in helping organizations derive actionable insights from data to drive business growth and decision-making. They combine technical expertise with business acumen to turn raw data into meaningful information that drives strategic initiatives and improves operational efficiency.

What do we offer?

Passion & fun

Besides our passion for insurance we believe in having fun from time to time, since happier employees perform better. Prepare for regular team updates & events and an exciting yearly calendar closing event (CCE)!

Training & Coaching

We strongly believe in training and coaching. Each employee receives a coach and a series of interesting trainings. We expect however the employee to play a pro-active role in this, outlining and managing his/her own career path. This may include taking internal responsibilities in a young company with ambitious growth plans.

Compensation & Benefits

We offer a full compensation & benefits package, consisting of an interesting salary, a motivating bonus scheme, representation and lunch allowances, eco-cheques, a cool company car with international fuel/electric card, a public transport subscription, a laptop, a deluxe smartphone and a hospitalization & group insurance.

What will you be doing?

1. Data Collection and Processing:

• Gather data from various sources such as databases, spreadsheets, and APIs.
• Clean and preprocess data to ensure accuracy and consistency.
• Organize and structure data for analysis.

2. Data Analysis:

• Apply statistical methods and analytical techniques to interpret data.
• Identify trends, patterns, and correlations in the data.
• Perform exploratory data analysis (EDA) to discover insights.
• Conduct hypothesis testing and statistical inference.

3. Data Visualization:

• Create visualizations such as charts, graphs, and dashboards to communicate insights effectively.
• Use tools like Tableau, Power BI, or matplotlib for data visualization.
• Design visually appealing and informative reports for stakeholders.

4. Reporting and Presentation:

• Prepare reports and presentations summarizing findings and insights.
• Communicate complex technical concepts in a clear and understandable manner.
• Present findings to stakeholders, including management and non-technical audiences.

5. Data-driven Decision Making:

• Collaborate with teams across the organization to understand business requirements.
• Provide data-driven recommendations and insights to support decision-making processes.
• Monitor key performance indicators (KPIs) and metrics to track progress and performance.

6. Continuous Learning and Improvement:

• Stay updated on emerging trends, tools, and technologies in data analysis.
• Enhance analytical skills through training, certifications, and hands-on experience.
• Share knowledge and best practices with colleagues to foster a culture of learning.

What do you need to bring?

• Proficiency in SQL for data querying and manipulation.
• Strong analytical and problem-solving skills.
• Strong experience within the Insurance Industry.
• Experience with statistical analysis and data visualization tools.
• Familiarity with programming languages such as Python or R.
• Knowledge of data warehousing concepts and data modeling.
• Excellent communication and presentation skills.
• Knowledge of Dutch and/or French, and English
• Attention to detail and ability to work independently.
• Bachelor’s degree in a relevant field such as statistics, mathematics, computer science, or related disciplines. A master’s degree or certifications in data analysis or related fields may be preferred.