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 hiring Data Analysts to help power a world of trust.

The Impact You’ll Make

At Incode, we’re building the future of digital identity verification through cutting-edge document intelligence and fraud detection technology. Our Document Intelligence and ID Document Verification teams are at the core of transforming how identification documents are processed and authenticated - from passports and IDs to driver’s licenses and proof of address.

We’re looking for Machine Learning Data Analysts to join our machine learning organization in these two teams. Depending on your background and interests, you may focus on data analytics, model performance evaluation, data pipelines, and ML data preparation. In both areas, you’ll work with large-scale datasets, collaborate with talented engineers and scientists, and help build reliable data systems that power Incode’s AI solutions.

What You’ll Own & Drive

• Analyze labeling quality and explain how it impacts model performance.
• Develop metrics and methods that align model evaluation with real-world use cases.
• Support internal tooling and monitoring to enable data-driven decisions.
• Prioritize work by impact and relevance to product goals.
• Contribute to tools for analysis, evaluation, and internal reporting.
• Work with large-scale data using Python and SQL, including AWS Redshift.
• Collaborate with ML engineers, analysts, and product stakeholders.

Your Background

• 3+ years of experience as a Data Analyst or similar role working with large-scale datasets.
• Deep understanding of data analysis principles, statistical reasoning, and ML concepts.
• Commitment to data accuracy, reliability, and quality.
• Strong written and spoken communication skills in English.
• Self-motivated, fast learner, able to manage multiple priorities effectively.
• Background in mathematics, physics, or engineering.

Document Intelligence Team

What You’ll Own & Drive – Team Focus

• Designing and implementing automated pipelines for data collection, labeling, and metric computation.
• Monitoring and ensuring data quality, labeling consistency, and accuracy.
• Building systems for automated metric calculation and performance tracking.
• Supporting ML engineers and analytics teams with reliable, well-structured data workflows.
• Using workflow orchestration tools (Airflow, Prefect, or similar) to manage pipelines.
• Writing clean, maintainable, and well-structured Python code for data processes.
• Ensuring scalability and reliability of the data infrastructure supporting ML training.

Your Background

• Strong Python programming skills with a focus on clean, maintainable code.
• Solid SQL knowledge and experience with columnar or cloud databases (e.g., AWS Redshift).
• Hands-on experience with workflow orchestration tools such as Airflow, Prefect, or Dagster.
• Proven experience in data quality control, data preparation, or ML data pipelines.
• Understanding of metric computation, data labeling, and automation in ML workflows.
• Nice to have: familiarity with big data technologies or data infrastructure optimization.

ID Document Verification Team

What You’ll Own & Drive – Team Focus

• Extracting, processing, and optimizing large datasets from AWS Redshift.
• Building Tableau dashboards to visualize model performance and operational metrics.
• Conducting A/B tests and applying statistical methods to evaluate model performance.
• Developing and maintaining datasets and metrics related to validation and fraud scoring.
• Creating tools to enhance model evaluation, monitoring, and reporting.
• Improving data infrastructure and pipelines for accuracy, scalability, and availability.
• Collaborating closely with ML engineers, analysts, and product teams to support data-driven decisions.

Your Background

• Strong background in data analysis, statistical testing, and model evaluation.
• Advanced SQL and Python (pandas, NumPy, matplotlib) for analytical workflows.
• Experience with Tableau (or similar BI tools) to visualize insights and metrics.
• Proven experience with A/B testing, statistical hypothesis testing, and result interpretation.
• Understanding of ML performance metrics such as accuracy, precision, and recall.
• Excellent communication skills to present analytical findings clearly.
• Nice to have: experience with fraud detection systems, fraud scoring, or labeling tools (e.g., Label Studio).

The Qualities That Set You Apart

• Analytical and technical - comfortable digging into data and understanding ML behavior.
• Ownership mindset - you prioritize by impact and bring clarity to complex problems.
• Data accuracy champion - you care about quality, reliability, and reproducibility.
• Clear communicator - you translate complex findings for any audience.
• Curious and proactive - you improve tools, metrics, and processes continuously.

Why Incode?

Mission with Meaning - Shape how billions of people prove identity - safely, simply, and ethically.
Rocket-Ship Growth - Join at an inflection point where your work compounds in impact.
Elite Team & Technology - Collaborate with world-class ML engineers and data scientists.
Ownership & Autonomy - Operate with the freedom to build and the support to deliver.
Global Impact - Your work will help power secure identity experiences across industries and continents.