Data Scientist, Finance Analytics

Job Description

Airtable is seeking a Data Scientist to join their Finance Analytics team. In this role, the Data Scientist will work directly with Airtable’s business stakeholders, providing strategic insights to navigate the financial landscape and ensure metrics align with the priorities of the CFO organization. This position offers a significant opportunity to impact Airtable's strategy and contribute to the company’s growth and success.Responsibilities:

• Champion data excellence for leadership within the CFO organization.
• Define business and financial metrics to address complex business challenges.
• Drive in-depth financial analysis to ensure the accuracy and relevance of key metrics.
• Develop and maintain high-quality dashboards and KPIs for real-time insights.
• Communicate the “so-what” of analysis to drive business impact across the organization.

Requirements:

• Bachelor's degree in a quantitative discipline; MS/MBA preferred.
• 4+ years of experience as a data scientist/analytics engineer in high-growth B2B SaaS.
• Demonstrated financial acumen with understanding of Enterprise go-to-market strategies and financial metrics.
• Familiarity with ERP & finance platforms (e.g., Workday, Pigment, Anaplan) and CRM platforms (e.g., Salesforce).
• 4+ years of experience with SQL in modern data platforms (e.g., Databricks, Snowflake, Redshift, BigQuery).
• 4+ years of experience with Python or R for analytics or data science projects.
• 4+ years of experience building business-facing dashboards and data models using modern BI tools (e.g., Looker, Tableau).
• Proficient-level experience developing automated solutions to collect, transform, and clean data using tools like dbt, Fivetran, etc.
• Some knowledge of data science models (e.g., regression, classification, clustering, time series analysis, experiment design).
• Excellent communication skills to present findings to both technical and non-technical audiences.

Airtable offers:

• Opportunity to impact company strategy and growth.
• Platform to deploy data skills in a meaningful way.
• Comprehensive benefit offerings.
• Restricted stock units.
• Incentive compensation.