About this role
The team is seeking a highly skilled Senior Data Analyst with strong domain expertise in Insurance and Financial Services. This role focuses on developing data-driven solutions across Fraud Detection, Risk Prediction, and Underwriting Analytics.
Key Responsibilities:
- Develop and deploy machine learning models for fraud detection, underwriting risk, and customer risk profiling.
- Build scalable data pipelines and feature engineering frameworks using Python and relevant technologies.
- Analyze large datasets to derive insights and support strategic decision-making.
- Collaborate with cross-functional teams to identify data needs and deliver actionable analytics.
- Monitor model performance and iterate on solutions to enhance accuracy and efficiency.
Required Skills & Qualifications:
- Proven experience in data analysis, machine learning, and statistical modeling.
- Strong programming skills in Python and experience with data manipulation libraries.
- Familiarity with data visualization tools such as Tableau or Power BI.
- Knowledge of database technologies like SQL and experience with big data tools.
- Excellent problem-solving skills and ability to communicate complex data insights clearly.
Experience: 5-7 years in data analytics, preferably within the insurance or financial services sector.
What we offer:
- Opportunity to work on impactful projects in a dynamic and growing industry.
- Collaborative work environment with a focus on professional development.
- Access to the latest tools and technologies in data analytics.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.