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Mid LevelFull-timePythonRustAWSMachine LearningGitAIML
Salary Range
$80,750 - $109,250 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Data Analyst to join our ID Document Intelligence team at Incode. This role involves designing and maintaining data pipelines that fuel our machine learning ecosystem, ensuring data flows efficiently through model training, labeling, and performance tracking.
Key Responsibilities
- →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, driving consistency checks, accuracy audits, and root-cause analysis.
- →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.
- →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 where needed.
- →Partner closely with ML engineers, analysts, and product stakeholders to prioritize work by impact and continuously improve internal tooling.
Requirements
- ✓3+ years of experience as a Data Analyst or in a similar data infrastructure role.
- ✓Strong Python programming skills with a 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 in ML workflows.
- ✓Strong collaboration and problem-solving skills.
- ✓Background in mathematics, physics, or engineering.
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