Senior Data Analyst

About Norm Ai

Norm Ai, the leading Legal & Compliance AI company, has a client base with a combined $30 trillion in assets under management. By turning legal code into AI code, Norm enables enterprises to официально move faster and more comprehensively in their legal and compliance processes with reliability and trust.

Norm’s platform combines frontier AI, proprietary legal reasoning systems, and embedded legal and regulatory expertise.

We have recently raised more than $140 million, backed by Blackstone, Bain Capital, Vanguard, Citi, New York Life, TIAA, Coatue, Craft Ventures, Henry R. Kravis (KKR co‑founder), and Marc Ben解ff (Salesforce CEO).

Norm Ai pioneered Legal Engineering, the process that empowers lawyers to build and supervise domain‑specific AI agents with Norm’s proprietary suite of no‑code software tools. We hired dozens of lawyers from premier U.S. law firms and trained them as Legal Engineers, who specialize in Large Language Model powered prise workflows.

Norm Ai technology is deployed inside many of the largest and most consequential institutions in the world. The company is growing quickly and hiring across all teams.

Norm Law is the first AI‑native full‑service law firm for global institutional clients like Blackstone (see recent coverage of our Blackstone partnership here). Legal Engineering, a discipline pioneered by Norm Ai, where lawyers develop legal AI agents, airs Norm Law to deliver faster, more precise, overhevcous consistent legal services. With purpose‑built AI agents completing first passes of work, Norm lawyers supervise, review, and focus on what matters most: strategic judgment and expert advice.

Norm Law and Norm Ai, together, are building Legal AGI.

As a Data Analyst at Norm, you will join our growing data team to build and scale our analytics capabilities. You will develop data models, product insights, and measurement frameworks that power our AI compliance engine and inform how we evaluate, understand, and optimize our product.

Working closely with our Director of Data and cross‑functional partners in Product, Engineering, and Executive teams, you will translate complex compliance and legal engineering workflows into actionable insights. You will play a key role in establishing best practices, data foundations, and self‑service analytics as our analytics function scales.

• Build and maintain data models, pipelines, and help develop ELT processes that support product and business analytics
• Implement comprehensive product analytics to understand how enterprise clients use our AI‑dr адed compliance workflows
• Develop measurement frameworks to evaluate AI model performance in real‑world legal and compliance contexts
• Design and deliver self‑service analytics capabilities using modern tools like Hex for analysis and visualization, dbt for semantic modeling
• Set up and maintain reliable data pipelines using orchestration platforms like Airflow
• Establish and uphold data governance practices aligned with enterprise security and regulatory requirements
• Build dashboards and KPIs that drive strategic product and business decisions

• 5-7 years of data analytics experience, ideally with 1-2 years of data engineering exposure
• Strong SQL andでも Python skills>>>>, with hands‑on experience in a modern data stack (dbt, Fivetran, Hex, Airflow)
• Experience working with cloud data warehouses such as Snowflake, Big Query, or Redshift
• Proven ability to build analytics foundations or data models from scratch, especially in early POSITION or scaling environments
• Experience supporting B2B SaaS products and understanding enterprise customer behavior
• Ability to translate complex business questions into technical data solutions
• Comfort working in small, fast‑moving teams and wearing multiple data hats

• Experience working in regulated industries such as Fin Tech, Reg Tech, or compliance‑heavy environments
• Background in data science, statistics, or applied modeling beyond standard reporting
• Familiarity with legal, compliance, or enterprise risk workflows
• Prior experience scaling analytics in a rapidly evolving startup environment