Senior Analytics Engineer (Antifraud)

Location: Remote; candidates may be based in Cyprus or the United Kingdom, with locations listed as Limassol, EU, CY and London, EU, GB. No mandatory office days; occasional in-person team offsites take place a few times per year.

Company

hirify.global provides AI-powered trust infrastructure for compliance operations, including identity and business verification, fraud prevention, transaction monitoring, and risk workflows.

What you will do

• Design, build, and evolve core anti-fraud analytics data models in ClickHouse and dbt.
• Create reliable, documented datasets and shared metrics for measuring and comparing detection performance.
• Own data quality through testing, documentation, lineage, and monitoring, and bring new data sources into the model with Data Engineering, Product, and anti-fraud experts.
• Analyze anti-fraud tools across products, clients, and fraud scenarios, and develop repeatable approaches for evaluating detection-logic changes.
• Turn analytical findings into clear recommendations for Product and clients, including support for complex data-intensive client cases.

Requirements

• 4+ years in analytics engineering, data engineering, or product analytics, with data modeling as a core part of the work.
• Expert SQL and strong data modeling skills, including dimensional modeling, event data, slowly changing dimensions, incremental models, and clearly defined table grain.
• Production experience with dbt or a comparable tool, including tests, documentation, incremental materializations, and code review.
• Hands-on experience with ClickHouse or another columnar warehouse and large event-level datasets.
• Strong Python for analysis and data work.
• Strong understanding of detection-quality evaluation, including confusion matrices, precision and recall, PR and ROC curves, threshold trade-offs, and the cost of errors.
• Ability to identify bias, leakage, and misleading metrics in imperfect data before they reach dashboards.
• Ability to explain findings to product managers and clients using clear logic, numbers, and concrete examples.
• Hands-on experience with AI tools in analytics and data engineering, or strong readiness to make them a core part of the work. Fluency in English is required.

Culture & Benefits

• Remote-first, trust-based work with no mandatory office days or attendance tracking; working hours are flexible rather than fixed to a 9-to-5 schedule.
• Birthday holiday, 10 personal days per year, seven sick days without paperwork, and additional Christmas and New Year time off.
• Role-specific learning opportunities and covered events, with clear goals, feedback, and personal development plans.
• Financial bonuses for marriage and welcoming a new baby, plus fully covered team offsites held a few times per year.
• Required work tools and hardware are provided, alongside an open, inclusive, and human working environment.

Hiring process

• TA screening.
• Interview with the Head of Product Analytics, followed by interviews with the Antifraud Product Manager and Director of Analytics.
• Compensation depends on confirmed work location and applicable local market conditions; the relevant range is shared during recruitment.