Senior Data Scientist / ML Engineer

About the role

Rho, a modern banking platform for startups and growth-stage companies, is looking for a Senior Data Scientist to join its data products team. The role has significant latitude to shape how modeling, evaluation and ML infrastructure work, and is intentionally hybrid: the person builds models and also reasons about how they are deployed, monitored and retrained in production. It works on projects such as a transaction coding suggestion engine, an OCR/document understanding pipeline and RAG-based and agentic systems.

Key responsibilities

• Help define and evolve ML/DS practices: how models are evaluated, deployed, monitored, versioned and retrained.
• Design and implement evaluation frameworks and eval harnesses that give confidence in model quality before and after launch.
• Build and own high-impact models and analyses for products such as transaction coding suggestions, OCR/document understanding and RAG/agentic systems.
• Make and document key ML infrastructure decisions (model registries, feature stores, serving patterns, monitoring and alerting for drift and degradation) with data engineering.
• Set technical standards and best practices so the practice scales as the team grows.
• Translate ambiguous business problems into well-scoped modeling questions.
• Design and analyze experiments (A/B tests, causal inference) to validate model impact.
• Advocate for and drive adoption of ML infrastructure and tooling improvements.

Required profile

• 6+ years of experience in data science, applied ML or a related quantitative field, with a track record of shipping models into production.
• Deep, hands-on understanding of ML infrastructure: model registries, feature stores, serving architectures, monitoring and retraining pipelines.
• Strong experience designing evaluation frameworks and evals, including offline metrics and ongoing production evaluation.
• Comfortable working as a hybrid DS/infrastructure practitioner and owning models end to end.
• Experience helping establish or mature ML practices, standards or infrastructure within a team and company.
• Experience with statistical modeling, ML techniques and experiment design.

Required skills

• Python and SQL
• Snowflake, DBT, PostgreSQL, Kubernetes, MLflow, Terraform, Prometheus, Google Cloud Services, Omni, Hex, PowerBI
• Nice to have: RAG, vector databases, agents, OCR, Airflow/Dagster/Prefect, GCP Vertex AI or AWS SageMaker, BI tools, fintech background, mentoring experience

What we offer

• Base salary depending on experience, skills, location and business needs
• Private healthcare insurance for you and your family
• Generous PTO, lunch at work and covered parking for onsite staff
• Learning and development budget, paternity leave
• Hybrid work with an office in old town Belgrade