About
Incode provides AI-powered identity verification solutions that help banks, fintechs, marketplaces, and governments deliver friction-free experiences while preventing fraud and safeguarding privacy. Its technology processes identity documents, including passports, visas, and driver's licenses.
Responsibilities
•Lead and grow the analytics team, own its roadmap, conduct 1:1s and performance reviews, develop analysts, and participate in hiring
•Write SQL and Python pipelines for data collection, processing, and labeling, and perform analyses
•Build an end-to-end metric tree to measure product quality across the document-processing pipeline
•Create reports and dashboards that surface weak points and turn raw signals into insights for ML, product, and leadership
•Drive ML data preparation, model quality assessment, and benchmarking with the ML team
•Design, run, and interpret A/B tests across mobile and server side
•Monitor data and labeling accuracy and consistency, and build quality controls
•Identify missing events or data, define what is needed and where it should come from, write actionable tasks for backend and data teams, and justify their priority in business terms
•Turn one-off analyses into repeatable pipelines and reporting cadences
Requirements
•Team leadership experience and willingness to stay hands-on
•Strong Python skills and ability to write clean, maintainable, well-structured code
•Strong SQL skills and solid experience with columnar or analytical databases
•Strong statistics and experimental design skills, including test design, statistical significance and power, and correct interpretation of results
•Experience with modern data tooling, including workflow orchestration, data transformation, cloud storage, and experiment tracking; equivalent tools to Python, S3, Redshift, ClearML, Airflow, and dbt are acceptable
•Excellent communication skills, including translating data gaps into prioritized, business-justified requirements and communicating with engineers and stakeholders
•High ownership, autonomy, and pragmatism; ability to prioritize impact over perfection in an evolving environment
•A player-coach mindset, craftsmanship in building clean code and reliable pipelines and analyses, intellectual honesty, and statistical rigor
Nice to have
•Experience with ML-centered products and model quality evaluation
•Ability to run existing models or simple models for data filtering
•Familiarity with data labeling and quality estimation or maintenance
•Exposure to identity documents, OCR, or computer-vision pipelines
Conditions
•Flexible working hours and workplace
•Open vacation policy
