Senior 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 Senior Data Scientist to help us make a real difference in the Fintech industry. Ready to join us and shape the future of payments? Let’s make it happen!

Job Responsibility

Own the full lifecycle of complex modelling programmes across Customer & Commercial Intelligence: CLTV, Churn Prediction, Propensity to Buy, and Next Most Likely Product (NMLP)
Architect multi-horizon churn models and build the churn intervention scoring layer that prioritises at-risk merchants for Account Management teams
Lead the NMLP engine — designing and productionizing a multi-output recommendation system that identifies the next product across myPOS's full catalogue
Take technical ownership of core fraud model components: transaction-level classifiers, merchant behaviour anomaly detectors, and new-account fraud scorers optimised for high-throughput, low-latency inference
Architect and own the Next Best Action (NBA) decisioning engine - a real-time system that selects the highest-expected-value action for each merchant at every interaction
Design and build production-grade agentic AI systems that automate high-value analytical and operational workflows
Define and execute experiment designs for online evaluation - A/B tests, uplift experiments, and bandits - and analyse results with statistical rigour
Set and enforce technical standards across the team: code quality, reproducibility, evaluation rigour, model documentation, and MLOps practices
Produce high-quality model documentation and present complex modelling work clearly to stakeholders across Sales, Marketing, Risk, Product, and Operations

Requirements

MSc or PhD in Computer Science, Statistics, Applied Mathematics, Econometrics or a related quantitative field (or equivalent commercial experience)
7+ years of applied data science and ML experience in a commercial environment, with a strong portfolio of models in production that drove measurable business outcomes
Expert Python for data science and ML engineering: pandas, scikit-learn, XGBoost / LightGBM, PyTorch or TensorFlow
clean, tested, modular code as a default
Deep expertise across the ML methodological spectrum: survival analysis, time-series and sequence modelling, uplift and causal inference, anomaly detection, and recommendation systems
Proven end-to-end ownership of at least three of: CLTV models, churn models, propensity models, fraud/risk models, recommendation or NBA systems - in a production commercial setting
Strong MLOps capability: feature stores, model registries, model serving infrastructure, drift monitoring, and CI/CD for ML pipelines
Deep SQL and data platform proficiency (GCP / BigQuery strongly preferred)
experience with streaming architectures for real-time feature generation
Hands-on expertise building LLM-powered applications: RAG pipelines, tool-use agents, multi-agent orchestration, and agent evaluation frameworks
Strong experience with causal inference methods: uplift modelling, difference-in-differences, or instrumental variables
Excellent communication: able to present complex technical work to senior business stakeholders and write high-quality model documentation

Nice to have

Experience in payments, fintech or financial services
Experience with reinforcement learning or contextual bandits for ranking and decisioning
Knowledge of graph neural networks for fraud or relationship modelling
Familiarity with AI governance frameworks (EU AI Act, SR 11-7)
Published research or open-source ML contributions
Experience with real-time streaming inference (Flink, Spark Streaming)

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
Teambuilding, social activities and networks on a multi-national level

myPOS - All Job Offers