Senior Data Scientist

Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed.

If you're a collaborator who wants to help transform how businesses operate globally, get in touch - we'd love to discuss how Ebury can accelerate your career so you can shape the future.

Location: Madrid (Hybrid: 4 days office / 1 day WFH)

Stack: Python, SQL, GCP (Big Query, AI Platform, Cloud Functions), ML Libraries, CRM (Salesforce), LLMs.

Ebury is executing an ambitious strategic growth plan across multiple business verticals. To power this expansion, we need to bridge the gap between advanced data science and real-world sales execution. This role exists to drive innovation in Growth modelling and deliver the actionable, data-driven insights that fuel our global sales engine.

Today, optimizing sales performance requires continuous experimentation and refining how we identify commercial opportunities. Tomorrow, we want to scale and seamlessly integrate our predictive models—such as Lead Scoring, conversion, and profitability models—directly into our sales enablement platforms so our teams can make faster, smarter, and highly optimized decisions every day.

• Drive innovation in Growth modelling by identifying opportunities for improvement, experimenting with new methodologies, and continuously refining models to enhance accuracy and performance.
• Develop and refine models for sales enablement and growth
  , using Python to drive better sales performance and decision-making. These models include, but are not limited to:
  Lead Scoring models, conversion models, profitability models, etc.
• Analyse and optimise sales data to identify patterns, trends, and opportunities that enhance lead scoring and sales strategies, contributing to overall business growth.

• Collaborate with Data Engineers and Sales Analysts to integrate models into sales enablement platforms, ensuring the delivery of actionable insights to sales teams and business stakeholders.
• Support the adoption of advanced analytics tools within the sales team, providing clear guidance on model outputs while working closely with senior data scientists for continuous improvement and learning.

• 5+ years of experience in Data Science or related roles
• Proficiency in Python and extensive experience with machine learning libraries.
• Solid understanding of statistical methods and machine learning models
  , with the clear ability to interpret model results and rigorously assess their performance.
• Excellent communication and collaboration skills
  , with the ability to work closely with data engineers, analysts, and business stakeholders to translate complex data insights into actionable business strategies.
• Experience collaborating with cross-functional teams (including Data Engineers, Sales Analysts, and business stakeholders) to ensure models align perfectly with business objectives.
• A problem-solving mindset with the ability to identify data-driven solutions to complex sales and growth challenges, helping optimize sales strategies and decision-making processes.
• Self-motivation and curiosity
  , with a strong desire to learn and grow in a fast-paced environment, continuously improving both technical and business skills.

• Experience with GCP (Google Cloud Platform) tools and services, such as Big Query, AI Platform, and Cloud Functions, for deploying scalable data solutions.
• Experience with A/B testing or experimentation frameworks is a plus, particularly for optimising sales strategies based on model performance.
• Knowledge of sales analytics and CRM systems
  , understanding how data insights can improve lead quality and sales outcomes (familiarity with tools like Salesforce is a plus).
• Expertise in leveraging Large Language Models (LLMs) for processing unstructured data, such as text analysis and sentiment analysis, to enhance risk assessment and decision-making.
• Proficiency in SQL for querying and managing large datasets, as well as experience working with both structured and unstructured data sources.
• Previous hands-on experience building lead scoring models, Customer Lifetime Value (CLV) models, and churn models.

• Competitive Salary +…