Business Analyst

𝐉𝐎𝐁 𝐒𝐔𝐌𝐌𝐀𝐑𝐘
As a Data Analyst, you will collaborate with teams across product, engineering, customer success, and business development to analyze key data such as usage patterns, partner performance, and insurance-related KPIs. Your insights will support internal decision-making and drive improvements in platform performance, enhancing outcomes for the clients.

𝐐𝐔𝐀𝐋𝐈𝐅𝐈𝐂𝐀𝐓𝐈𝐎𝐍𝐒, 𝐒𝐊𝐈𝐋𝐋𝐒 & 𝐄𝐗𝐏𝐄𝐑𝐈𝐄𝐍𝐂𝐄:
1. 2–4 years of hands-on experience in data analysis, ideally within a SaaS, fintech, or insurance setting.
2. Proficiency in SQL, Excel/Google Sheets, and at least one data visualization tool (e.g., Power BI, Looker, Tableau).
3. Familiarity with Python or R for data manipulation is a plus.
4. Strong understanding of relational databases and experience working with APIs or JSON files.
5. Comfortable navigating ambiguity in fast-paced, cross-functional environments.
6. Exceptional analytical skills with a keen eye for detail and the ability to translate business needs into analytical questions.
7. A background in insurance or an understanding of insurance workflows (underwriting, claims, pricing) is highly desirable.

𝐉𝐎𝐁 𝐑𝐄𝐒𝐏𝐎𝐍𝐒𝐈𝐁𝐈𝐋𝐈𝐓𝐈𝐄𝐒:
1. Gather, clean, and analyze large datasets from internal systems, including SaaS platforms, APIs, logs, and partner databases.
2. Develop and maintain dashboards and reports for both internal and external stakeholders using tools like Power BI, Tableau, or Google Data Studio.
3. Monitor key product and operational metrics such as quote-to-bind ratio, policy issuance time, claim trends, and renewal patterns.
4. Identify and analyze data-driven trends across different markets, customer segments, and product lines (e.g., motor, health, life).
5. Assist pricing and actuarial teams by preparing well-structured datasets for further analysis.
6. Work with product managers and engineers to define key metrics and assess the performance of new features.
7. Partner with the customer success team to generate partner insights and performance summaries.
8. Contribute to data governance, quality assurance, and documentation processes.