Data Science Manager (Credit)

Moniepoint, BRM; España; Híbrido; EUR 90.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Financial inclusion impact

Innovative projects

Diverse environment

Flexible work arrangements

Continuous learning

Performance bonuses

Health insurance

Pension plans

Descripción de la vacante

Moniepoint in Spain is seeking a hands-on Data Science Manager to lead our consumer credit data science efforts in a high-growth environment. This role owns pricing, credit limit modelling, and deployment of production credit models, with impact on millions of customers.

You will partner with Consumer Credit, Product, and Engineering to shape risk assessment, pricing, and product design, building analytics foundations for underwriting, acquisition, retention, and portfolio performance.

Formación

• Degree in a quantitative field (Statistics, Mathematics, Engineering or similar).
• 5+ years of experience in data science, decision science, or risk analytics with at least 2+ years in management.
• Working knowledge of credit risk, consumer lending, and regulatory considerations.
• Proficiency in SQL and at least one modelling/programming language (Python, R).
• Experience with A/B testing, machine learning, collections modelling and churn management.
• Ability to translate complex analyses into clear recommendations for business stakeholders.
• High ownership mindset and comfort working in fast-paced, cross-functional teams.

Responsabilidades

• Develop credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections.
• Design and run experiments to optimise approval rates, loss rates, and profitability.
• Partner with product squads to embed decision logic into real-time systems.
• Ensure data quality, compliance, and ethical use of models across all decisioning processes.
• Mentor product squads on best practices in experimentation and data‑driven decision making.
• Provide models to optimise outcomes in collections, churn management and user retention.

Conocimientos

Data science

Management

Credit risk

SQL

Python

R

A/B testing

Machine learning

Collections modelling

Churn management

Communication

Ownership

Cross-functional collaboration

Educación

Statistics/Mathematics/Engineering or similar

Descripción del empleo

Who We Are

Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools – reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.

Our mission is simple: to enable financial happiness for every African, everywhere. We’ve grown rapidly in Nigeria and UK, and we’re now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets – solving real, meaningful problems at scale.

We onboard over a million new customers each month, process hundreds of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our teams operate in a fast‑paced, high‑impact environment alongside international leaders from companies like Glovo, Bolt, Monzo, Klarna, Checkout.com, and Tide. If you want to build our data science function from the ground up, work with one of Africa’s highest‑scale fintech data sets, and ship products that influence tens of millions of users, this is an exceptional time to join.

About The Role

We’re looking for a hands‑on, Spain‑based Data Science Manager to lead our consumer credit data science efforts in a high‑growth environment. This role is pivotal in building and scaling a team responsible for pricing, credit limit modelling, and production credit model deployment, with direct ownership of decisions that impact millions of customers.

You’ll work closely with our Consumer Credit, Product, and Engineering teams to shape how we assess and price risk, design credit products, and measure outcomes across the credit lifecycle. Sitting at the intersection of data science, credit risk, and product, you’ll build the analytics and modelling foundations that inform underwriting, customer acquisition, retention, and portfolio performance at scale.

Day‑to‑Day Responsibilities

• Develop credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections.
• Design and run experiments to optimise approval rates, loss rates, and profitability.
• Partner with product squads to embed decision logic into real‑time systems.
• Ensure data quality, compliance, and ethical use of models across all decisioning processes.
• Mentor product squads on best practices in experimentation and data‑driven decision making.
• Provide models to optimise outcomes in collections, churn management and user retention.

Qualifications

• Comfortable with Statistics, and have a degree or qualifications in a quantitative field (Statistics, Mathematics, Engineering or similar).
• +5 years of experience in data science, decision science, or risk analytics within financial services, including +2 years in management.
• Working knowledge of credit risk, consumer lending, and regulatory considerations.
• Proficiency in SQL and at least one modelling/programming language (Python, R).
• Experience with A/B testing, machine learning, collections modelling and churn management.
• Ability to translate complex analyses into clear recommendations for business stakeholders.
• High ownership mindset and comfort working in fast‑paced, cross‑functional teams.

Benefits

• The opportunity to drive financial inclusion and shape the future of the African financial ecosystem.
• The chance to work on innovative and impactful projects.
• A dynamic, diverse, and collaborative environment where every team member’s voice is recognized and valued.
• Flexible work arrangements.
• Continuous learning and career growth opportunities.
• Competitive salary, individual performance bonuses, and firmwide performance bonus.
• Company‑covered health insurance plans.
• Pension plans.

Hiring Process

• Introductory call with one of our recruiters.
• Initial interview with the Director of Data Science.
• Take‑home task (hands‑on coding or marketing modelling case study).
• Business case interview with our Head of Marketing Strategy & Data.
• Live technical coding interview with the Director of Data Science.
• Culture & values interview (60 minutes) with the Director of Data Science.

Moniepoint is an equal‑opportunity employer. We believe diversity makes us stronger and are committed to creating an inclusive environment for all employees and candidates.