Data Scientist

Join Wandoo Finance as a Data Scientist and help challenge the status quo of the financial industry

We are a fast growing global fintech powerhouse – with HQ in Latvia and operations across Poland, Spain, Romania, Peru and now also Lithuania. We deliver innovative financial solutions across borders, combining tech-driven thinking with global reach.

As our business grows and expands into new markets, our Data Science team faces exciting challenges — building new models, improving existing ones, and creating smarter solutions. This is where you come in.

If you enjoy working with data, building machine learning models, and seeing your solutions deployed in real business environments, this role will give you the freedom, ownership, and impact you’re looking for.

How You’ll Make an Impact

• Machine learning development: build, test, and improve machine learning models to support risk, underwriting, and product optimisation.
• ML pipeline automation: develop and maintain automated pipelines for model training, feature generation, hyperparameter tuning, and deployment.
• Data extraction & preparation: collect and structure data from multiple sources including data warehouses, production databases, third-party providers, and public datasets.
• Feature engineering: design and evaluate statistical features, perform time-series extraction, and ensure high-quality feature selection and cleaning.
• Model evaluation & benchmarking: generate model performance metrics, compare alternative models, and ensure robust validation practices.
• Model deployment & monitoring: support model deployment to production environments and continuously monitor performance, stability, and drift.
• Data analysis & insights: analyse datasets to identify patterns and provide insights that support product development, credit decisioning, and risk management.
• Product optimisation: provide data-driven recommendations to improve underwriting policies, product performance, and decision-making processes.
• Performance dashboards: develop and maintain dashboards for monitoring model performance, metrics, and configurable model parameters.

• 3+ years of experience developing machine learning models using Python
• Time-series expertise: demonstrated experience analysing and applying time-series data in machine learning models.
• Tech stack: strong proficiency in Python, SQL, and Docker for data processing, modelling, and deployment.
• ML pipeline automation: experience building and maintaining automated machine learning workflows using Airflow or similar orchestration tools.
• Model monitoring & maintenance: experience monitoring production models, including population stability, feature stability, and explainability techniques such as SHAP.
• Modelling expertise: hands-on experience developing models using GBM, XGBoost, and other tree-based boosting algorithms

Priekšrocības

• Nice to have: experience working with Google Cloud, Java, or FastAPI

• A competitive monthly salary starting from 3500 EUR gross, depending on your experience
• Hybrid life- 3 days in the office, 2 days in your personal kingdom
• Workcation- enjoy up to 2 weeks per year working from anywhere
• Annual bonus & salary review once a year - because progress matters
• Learning & growth opportunities chose by you, approved by us
• Birthday off- your day, your rules
• 5 paid blood donor days- superheroes deserve time off
• Health insurance after probation- extra coverage to keep you fully protected