Senior Applied Data Scientist

The role

You will lead the design and productionization of statistical and ML models for risk scoring, fraud detection, and transaction categorization. You will turn financial data into models that drive real financial outcomes and own them from notebook to production.

What you will do

• Lead the design of statistical and ML models for risk scoring, fraud detection and transaction categorization
• Use agentic coding and research tooling to explore data and scaffold pipelines
• Translate ambiguous business questions into well-scoped modeling problems
• Build and shape pipelines, APIs and services to run models in production
• Own models in production including monitoring, drift, retraining, and retirement
• Design and run experiments such as A/B tests and offline evaluation
• Work with Engineering, Data Research, Product, and stakeholders to ship end to end
• Explain trade-offs and impact to non-technical audiences and executives
• Stay current with GenAI model releases, papers, and tooling
• Decide which problems are worth modeling and push back when a rule or heuristic is better

Required qualifications

• 5+ years of experience as a Data Scientist, Applied Scientist, or in a similar hands-on modeling role
• Owned models end to end in production with measurable business impact
• Solid grounding in statistics
• Built and compared more than one type of model for the same problem
• Comfortable in Python for data science (pandas, scikit-learn, and at least one of TensorFlow or PyTorch)
• Proficient in SQL for pulling and shaping data
• Taken several models built into production yourself
• Understand engineering fundamentals: testing, version control, CI/CD
• Built with LLMs past the API-call level including tool use, agents, retrieval, or structured outputs
• Use agentic coding tools in daily workflow
• Proficient in written and spoken English

Nice to have

• Worked in fintech, financial risk, or another regulated data environment
• Business or strategy background (MBA, consulting, or a product/strategy role)
• Worked in a customer-facing data science role
• Worked with MLOps tooling for model versioning, monitoring, and automated retraining
• Deployed models on AWS
• Written evals or an LLM-as-judge harness for a non-deterministic system
• Used LLMs inside the data pipeline itself

Benefits

• Stock options
• Annual company bonus linked to company performance
• Flexible working hours
• Remote friendly
• Pet friendly
• Health Insurance
• Paid time off on your birthday
• Renew your laptop every 3 years
• Training Budget
• Team building events
• Bank holidays swap within 30 days
• Fitness/ wellness stipends

Before you apply

• People team chat
• Take-home challenge
• Challenge presentation
• Team fit chat
• Meet the founders

About the company

Belvo is an open finance API platform that enables financial innovators to access and interpret financial data in Latin America. The team is highly-technical, passionate, and driven, with over 90 people representing 20 nationalities.