Data Analyst

A LegalTech company has developed an innovative digital platform for case management, featuring a client-facing app, real-time updates, and transparent stage-based pricing providing a legal experience that is accessible, trustworthy, and user-friendly.

The U.S.-based company was founded five years ago with the mission to fundamentally transform how people experience legal services.

The company collaborates with hundreds of lawyers across the U.S. and has already served over 70,000 clients, primarily in family and immigration law. To date, it has raised around $200M, with a valuation exceeding $1B.

Based in Tel Aviv, the company operates a hybrid work model one remote day per week for local employees, and two days for those living outside the city. Today, it employs approximately 300 people globally, including 80 engineers at its Israel site.

The Role:

Reporting to the Head of Data, the position joins a team of three analysts within the product teams. Responsibilities include analyzing data, gaining deep insights into user behavior, identifying opportunities for improvement, and supporting strategic decision-making. The role involves close collaboration with Product Managers and working with SQL, A/B testing, KPIs, and Tableau.

Requirements:

• 5 years of experience in a similar data analyst role.
• Strong proficiency in SQL (mandatory).
• Experience analyzing B2C data.
• Excellent storytelling and communication skills, with the ability to build productive relationships with a diverse set of stakeholders.
• Experience with A/B testing and data visualization tools (e.g., Tableau, Power BI).
• Strong numerical and business acumen knowing when to use a single metric versus building a complex forecasting model.
• Ability to tackle ambiguous problems and challenges independently.
• Passion for understanding user behavior, leveraging all available methods, and advocating for a user-centered approach in product development.
• Curious, independent, and rigorous in approach.
• Technical skills to perform advanced analytics on large datasets using technologies such as Python, Pandas, or R considered an advantage.