Data Analyst Middle/Middle+ [Risk]
We are looking for a Data Analyst for our Risk AI Platform - the group that owns the data and ML infrastructure behind Plata's credit decisioning. At the center of that infrastructure is our feature store: the system that turns raw external and internal data into the features that power our scoring models, both in research and in real-time production.
The role sits at the intersection of data engineering, analytics, and ML: you'll spend most of your time in SQL, dbt, Python, and Snowflake, building reliable pipelines and making sure the features our models consume are correct, consistent, and well-monitored - offline and online.
Challenges that await you:
- Develop and maintain the feature store: design and optimize dbt models across our multi-layer pipeline, from raw ingestion through parsing, unification, and domain modeling to production-ready feature sets.
- Onboard new external data sources (credit bureaus, alternative data, identity and scoring providers) into the platform — from raw parsing to production features.
- Guarantee consistency between training and serving: build checks and monitoring that catch feature drift, mismatches, and data-quality issues before they reach a model.
- Own data quality and observability for the features you ship — freshness, completeness, lineage, and reconciliation.
- Work closely with data scientists and ML engineers to productionize features for scoring models, and help turn research feature logic into robust, tested pipeline code.
- Improve our tooling, standards, and documentation so the whole team ships features faster and more safely.
What makes you a great fit:
- 2-3 years of experience in a data engineering, analytics engineering, or strongly engineering-oriented data analyst role.
- Strong SQL: you're comfortable writing and optimizing complex queries.
- Solid Python for data work (data pipelines, scripting, pandas).
- Hands-on experience with dbt, or with building ETL/ELT pipelines you can map onto dbt.
- A working understanding of ML — enough to reason about features, training/serving consistency, and how your pipelines feed a model.
- A data-quality mindset: you care about correctness, reproducibility, and monitoring, not just getting the number out.
- B1 or higher English level for effective communication with an international team
Your bonus skills:
- Background in Risk, credit, lending, or fintech.
- Experience with Snowflake (or a comparable cloud data warehouse) and a cloud platform (AWS).
- Familiarity with feature stores, ML model registries.
- Comfort with A/B testing and applied statistics.
- Experience with orchestration and CI/CD for data.
- Innovative Spirit: A commitment to creativity and groundbreaking solutions
- Honest Feedback: valuing open, transparent communication
- Supportive Team: a strong, collaborative community
- Celebrating Achievements: recognizing our wins together
- High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances
Our benefits:
- Relocation support to one of our hubs — Cyprus, Serbia, Georgia or Kazakhstan — with assistance for the employee and their family
- Flexible work from one of our offices or remote
- Healthcare Coverage
- Education Budget: Language lessons, professional training and certifications
- Wellness Budget: Mental health and fitness activity reimbursements
- Vacation policy: 20 days of annual leave and paid sick leave