Data Scientist Job at myPOS (Sofia)

Job Description

At myPOS, we’re all about helping businesses grow and get paid. We make payments simple, smart, and accessible for everyone, but we’re more than just payment solutions - myPOS is a partner in growth. From free multicurrency accounts to powerful e-commerce tools, we’re here to support business owners of all sizes and everyone out there who dreams of starting their own business. As we are expanding our team, we’re looking for Data Scientist to help us make a real difference in the Fintech industry.

Job Responsibility

Build and maintain ML models across the core portfolio: CLTV, churn prediction, propensity to buy, and Next Most Likely Product (NMLP)
Develop fraud detection models including transaction-level classifiers, merchant behaviour anomaly detectors, and new-account risk scorers
Contribute scored model outputs to the Next Best Action (NBA) decisioning layer that selects the optimal action for each merchant across Sales, Marketing, and in-product touchpoints
Support A/B experiments, uplift tests, and multi-armed bandit evaluations to measure the incremental impact of model-driven interventions
Design and implement end-to-end ML pipelines — from data ingestion and feature engineering through to model training, evaluation, and deployment
Monitor deployed models in production: detect performance degradation, data drift, and data quality issues
iterate and document changes proactively
Collaborate with business teams across Sales, Marketing, Risk, Operations, and Product to translate business problems into well-defined data science solutions
Run rigorous experiments and communicate findings clearly to both technical and non-technical stakeholders
Contribute to LLM-powered agentic workflows using tool-use patterns (RAG, function calling, memory) and frameworks such as LangChain or LlamaIndex
Contribute to team documentation: model cards, methodology write-ups, and internal playbooks that help the team scale its practices

Requirements

3–5 years of hands-on applied data science, machine learning or statistical modelling experience in a commercial setting, with models shipped and measured in production
Strong proficiency in Python for data science: pandas, numpy, scikit-learn, XGBoost / LightGBM, and at least one deep learning framework (PyTorch or TensorFlow)
Solid grounding in supervised and unsupervised learning: classification, regression, clustering, survival analysis, and time-series modelling
Demonstrable experience building at least one of: CLTV, churn, fraud detection, propensity, or uplift models in a production environment
Comfort working with large-scale structured and semi-structured data
proficient in SQL and cloud data warehouses - GCP and BigQuery strongly preferred
Familiarity with ML experiment tracking platforms (MLflow, Weights & Biases) and model serving patterns (REST APIs, batch inference pipelines)
Working knowledge of LLM APIs (OpenAI, Anthropic, etc.) and at least one agentic AI framework (LangChain, LlamaIndex, AutoGen, or similar)
Understanding of responsible AI: fairness assessment, model explainability methods (SHAP, LIME), bias detection and mitigation strategies
Clear communication — able to distil statistical findings into actionable insights for both technical peers and business stakeholders

Nice to have

Experience in fintech, payments, banking or e-commerce
Familiarity with workflow orchestration (Airflow, Prefect, Dagster)
Exposure to causal inference methods (DiD, IV, PSM)
Experience building or fine-tuning LLMs, RAG pipelines, or tool-use agents
Knowledge of graph-based fraud detection techniques
Exposure to streaming feature engineering (Kafka, Pub-Sub, Spark)

What we offer

Excellent compensation package
25 days annual paid leave (+1 day per year up to 30)
Full “Luxury” package health insurance including dental care and optical glasses
Meal vouchers of 102.26 EUR per month
Fully covered Multisport card
Fully covered public transport pass for Sofia
Free coffee, snacks and drinks at the office
Annual salary reviews, promotions and performance bonuses
myPOS Academy for upskilling and training
Unlimited access to courses on LinkedIn Learning
Annual individual training and development budget
Refer a friend bonus as we know that working with friends is fun
Teambuilding, social activities and networks on a multi-national level

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