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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying statistical and machine learning models, with a strong focus on risk scoring and fraud detection. Proficient in Python, SQL, and LLM solutions, with a solid understanding of statistics and model evaluation.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProficiencySQL Data ManipulationModel Deployment on AWSStatistical Analysis
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical ModelingMachine LearningDeep LearningTree-Based MethodsRegression AnalysisFeature EngineeringA/B TestingModel MonitoringData Pipeline DevelopmentLLM Evaluation
Soft Skills
CollaborationCommunicationProblem-SolvingStakeholder EngagementTechnical Explanation
Tools & Technologies
PandasScikit-LearnTensorFlowPyTorchMLOps ToolingAgentic Coding ToolsCI/CDVersion ControlAPIsAWS
Industry Keywords
FintechFinancial RiskRegulated Data EnvironmentData ScienceCustomer-Facing ExperienceBusiness StrategyConsultingProduct ManagementModel EvaluationLive Model Monitoring
Tech Stack
Tools & technologiesAWSPandasPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Lead the design of statistical and machine learning models for risk scoring, fraud detection, transaction categorization, and related problems
- Use agentic coding and research tooling to explore data, generate and test feature hypotheses, scaffold pipelines, and write model services
- Partner with Product and business teams to identify meaningful signals and define well-scoped modeling problems
- Build or shape production pipelines, APIs, and services for models
- Own live models, including monitoring, drift detection, retraining, and retirement
- Design and run A/B tests and offline evaluations
- Collaborate with Engineering, Data Research, Product, Intelligence Squad, and business stakeholders
- Work directly with stakeholders and customers when needed
- Explain technical trade-offs and business impact to non-technical audiences and executives
- Stay current on GenAI model releases, papers, and tooling, sharing useful findings through demos, documentation, or AI Chapter sessions
- Decide which problems are worth modeling and use rules, heuristics, or improved data pipelines when they are more appropriate
- Participate in the hiring process through team-based interviews and assessments
Requirements
What you’ll need- 5+ years of experience as a Data Scientist, Applied Scientist, or in a similar hands-on modeling role
- Experience owning models end to end in production, from problem framing to live monitoring, with measurable business impact
- Solid grounding in statistics and ability to explain model workings at that level
- Experience building and comparing multiple model types, such as tree-based methods, regression, and deep learning
- Proficiency in Python for data science, including pandas, scikit-learn, and at least one of TensorFlow or PyTorch
- Proficiency in SQL for pulling and shaping data
- Experience taking several self-built models into production
- Understanding of testing, version control, CI/CD, and maintainable code
- Experience building LLM solutions beyond API calls, including tool use or agents, retrieval, structured outputs, and at least one production deployment
- Experience creating evaluations for LLM systems
- Daily use of agentic coding tools
- Proficient written and spoken English
- Fintech, financial risk, or regulated data environment experience is advantageous
- Business or strategy background, such as an MBA, consulting, or product/strategy role, is advantageous
- Customer-facing data science experience is advantageous
- Experience with MLOps tooling is advantageous
- Experience deploying models on AWS is advantageous
- Experience writing evaluations or an LLM-as-judge harness is advantageous
- Experience using LLMs in data pipelines is advantageous
Benefits
Comp & perks- 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
- Yearly company offsite
- Fresh fruit every week, all-you-can-drink tea and coffee
- Extra days off accrued when completing 2, 3, 4 years and beyond at Belvo
- Yearly department offsite