Machine Learning Data Analyst

About Incode

Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security.

Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we’re scaling fast - and we’re looking for data professionals passionate about building the pipelines and systems that power world-class ML models.

The Impact You’ll Make

As a Data Analyst on the ID Document Intelligence team, you’ll design and maintain the data pipelines that fuel Incode’s machine learning ecosystem. You’ll ensure that data flows efficiently and accurately through every stage of model training, labeling, and performance tracking.

Your work will be essential to maintaining the scalability, quality, and precision of Incode’s document intelligence systems used by millions worldwide.

What You’ll Own & Drive

• Design, build, and maintain automated data pipelines for collection, labeling, validation, and metric computation that support ML training and evaluation.
• Establish and monitor data and labeling quality standards - drive consistency checks, accuracy audits, and root-cause analysis when issues impact model outcomes.
• Define, implement, and automate model evaluation metrics and reporting that reflect real-world product use cases and business goals.
• Build scalable systems for performance tracking, dashboards, and monitoring to enable fast, data-driven decisions across teams.
• Develop and operate reliable workflow orchestration (Airflow, Prefect, or similar) to schedule, observe, and troubleshoot end-to-end pipelines.
• Write clean, maintainable Python code and performant SQL to process large datasets, leveraging AWS Redshift (and related AWS tooling) where needed.
• Partner closely with ML engineers, analysts, and product stakeholders to prioritize work by impact, unblock execution, and continuously improve internal tooling for analysis and evaluation.

Your Background

• 3+ years of experience as a Data Analyst or in a similar data infrastructure role.
• Strong Python programming skills with focus on clean, maintainable code.
• Solid SQL expertise and experience with cloud or columnar databases (e.g., AWS Redshift).
• Hands-on experience with workflow orchestration tools (Airflow, Prefect, Dagster, etc.).
• Proven experience in data quality management, data preparation, or ML data pipelines.
• Understanding of metric computation, data labeling, and automation<