Senior Data & Machine Learning Engineer
Primary stack
Job description
About the Position
Senior Data & Machine Learning Engineer
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Salary
55,000€ - 75,000€
Skills
- Python
- SQL
- AWS
- Docker
- MLflow
- FastAPI
- SQLAlchemy
- Pydantic
Location
Barcelona, Spain
Madrid, Spain
Languages
- Basic Spanish
- Fluent English
About the Position
We are looking for a Senior Data & Machine Learning Engineer to join our team at Novicap, an end-to-end working capital solutions provider focused on enabling CFOs/Finance teams of SMEs to pay their suppliers and collect from their customers. This includes short-term credit (factoring, supply chain finance and loans) and payment automation solutions.
With offices in Barcelona and Madrid, we are one of the fastest-growing fintech startups in Europe. Amazing, isn’t it? 🤓
Responsibilities
As a Senior Data & Machine Learning Engineer, you will:
Productionize credit risk and fraud models
- Work closely with the Data Science team to productionize Data Science solutions
- Own the full ML lifecycle: feature engineering, training and retraining workflows, model versioning (MLflow), and live monitoring for drift and degradation.
- Ensure deployed models meet the performance and latency standards required by automated credit decision workflows.
Design and deliver data services and products
- Build internal APIs to expose credit scoring, risk signals, and underwriting features - consumed by the Novicap platform, operational teams, and third-party partners.
- Model and maintain database schemas for credit products: scoring results, decision logs, exposure tracking, repayment history - optimized for both operational and analytical access.
- Own the data layer for new products (micro-credit, portfolio factoring, supply chain finance) from scratch: define the business logic, model the data, and implement end-to-end pipelines.
Build for scalability and reliability
- Design systems that grow with credit volumes and new product types - without requiring hard architectural rework every time.
- Apply software engineering best practices: modular code, unit and integration tests, CI/CD pipelines, clear documentation.
- Containerize and deploy services on AWS with Docker; orchestrate batch workflows (scoring runs, data refresh) with tools like Airflow.
Collaborate closely across teams
- Data Scientists: iterate rapidly on productionization - you are their engineering partner, not just a deployment step.
- Software Engineers: integrate data services into the platform cleanly, with clear API contracts and stable interfaces.
- Credit, Risk and Underwriting teams: translate operational needs into robust data product requirements.
Requirements
- End-to-end ML & data engineering: At least 3 to 5 years of experience in shipping Data Science solutions into production: feature pipelines, training and retraining workflows, model versioning, and live monitoring. Not prototypes - real systems that users and workflows depend on.
- Python & modern data frameworks: Clean, modular, testable Python is your default. Comfortable with FastAPI, SQLAlchemy, Pydantic and similar libraries; you know the difference between code that works and code that ships.
- Data services & APIs: Hands-on building internal REST APIs: request validation, async patterns, error handling, OpenAPI docs. You design stable contracts and think about versioning and performance from day one.
- Data modeling & SQL: Strong database skills across operational and analytical workloads: schema design, indexing, partitioning, query optimization. Comfortable modeling finance-domain data - scoring outputs, decision logs, exposure and repayment history.
- Cloud & infrastructure: Solid AWS cloud experience (S3, RDS, EC2, Lambda, IAM, others) deploying and operating APIs and batch workers. Comfortable containerizing workloads with Docker.
- Ownership & business acumen: Small team, high autonomy. You drive work from problem definition to production with minimal guidance, and you measure quality in terms of credit decisions - not just technical correctness.
We Offer
- Full-time work with an open-ended contract
- Hybrid work model: 3 days in the office and 2 days from home
- Flexible benefits with Coverflex: include monthly expenses for food, transportation, daycare, and others in your paycheck
- Medical insurance: optional health insurance through Sanitas, with competitive rates and Novicap subsidizing 30%
- Free English or Spanish classes to improve communication with colleagues
- Gym membership with Urban Sports Club, partly subsidized by Novicap
- Incredible and highly motivated co-workers
- Participation in company events and meetings with the rest of the team
- Dynamic and international work environment with a flat hierarchy and open communication between teams
- Library with plenty of books to choose from
- Free fruit, coffee, and tea in the office
About the Company
Novicap is an end-to-end working capital solutions provider focused on enabling CFOs/Finance teams of SMEs to pay their suppliers and collect from their customers. This includes short-term credit (factoring, supply chain finance and loans) and payment automation solutions.
With offices in Barcelona and Madrid, we are one of the fastest-growing fintech startups in Europe. Amazing, isn’t it? 🤓
Hiring Process
- First screening online interview with Hiring Manager (30min)
- Complete a 'data challenge' at home in your free time and send it back to us
- Group online interview to discuss data challenge (1h)
- HR online Meeting (30min)
- CEO online meeting (30min)
Contact Information
Location
Avinguda Diagonal, 618, Barcelona, Spain
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