обновлено 20 дней назад
Data Analytics Team Lead (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Analytics Team Lead (Python/SQL): Building data pipelines, metric trees, dashboards, and experimentation frameworks to measure the quality of ML-powered identity document processing with an accent on statistical rigor, labeling quality, and analytical visibility. Focus on evaluating ML models, designing A/B tests, systematizing reporting, and translating data gaps into prioritized engineering requirements.
Location: Serbia
Company
builds AI-powered identity verification and security solutions for banks, fintechs, marketplaces, governments, and other enterprises.
What you will do
- Lead and develop a three-person data analytics team, owning its roadmap, 1:1s, performance reviews, mentoring, and hiring.
- Write Python and SQL pipelines for data collection, processing, labeling, and analysis.
- Build an end-to-end metric tree and reporting dashboards for document-processing product quality.
- Prepare data for ML, evaluate model quality, and benchmark results in collaboration with the ML team.
- Design, run, and interpret statistically rigorous A/B tests across mobile and server-side products.
- Identify missing events and data, define actionable requirements for backend and data teams, and turn one-off analyses into repeatable pipelines and reporting cadences.
Requirements
- Experience leading a team while remaining hands-on with analytics implementation.
- Strong Python and SQL skills, including experience with columnar or analytical databases.
- Strong statistics and experimental design skills, including significance, statistical power, and correct result interpretation.
- Experience with workflow orchestration, data transformation, cloud storage, and experiment tracking; the stack includes Python, S3, Redshift, ClearML, Airflow, and dbt.
- Excellent communication skills for translating data gaps into prioritized, business-justified requirements.
- High ownership, autonomy, pragmatism, and the ability to prioritize impact in an evolving environment.
Nice to have
- Experience with ML-centered products and model quality evaluation.
- Familiarity with data labeling processes and quality estimation or maintenance.
- Exposure to identity documents, OCR, or computer-vision pipelines.
Culture & Benefits
- High-performance culture with freedom and responsibility.
- Autonomy to test, build, and ship ideas end-to-end.
- Continuous feedback, development opportunities, and promotions.
- Flexible working hours and workplace.
- Open vacation policy.
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