Senior Data Scientist
Ebury is hiring a Senior Data Scientist in Madrid, Spain. Level rates it ; you can apply on Ebury.
Level's read on this job
- On Level's scale, this data scientist role is Uses AI ●●○○: an ordinary role that requires AI tools.
- The posting mentions Vertex AI and AI evaluation among its tools and skills.
- Level classes it as a senior role.
- Ebury has 147 other open roles on Level.
- Posted in the last few days.
AI in this role
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.
Senior Data Scientist
Location: Madrid (Hybrid: 4 days office / 1 day WFH)
Stack: Python, SQL, GCP (BigQuery, AI Platform, Cloud Functions), ML Libraries, CRM (Salesforce), LLMs.
Why This Role Exists
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.
What You'll Do
- Roadmap & Ownership: Lead the commercial analytics data science roadmap end-to-end, taking full ownership from problem framing and experimentation through to production deployment and impact evaluation.
- Predictive Modeling: Evolve existing lead scoring and conversion models while designing and deploying novel predictive algorithms.
- Impact Measurement: Design and execute experimentation frameworks (A/B testing, causal inference) to rigorously quantify real-world revenue and sales impact.
- Workflow Integration: Collaborate with Data Engineers, Analytics Engineers, and Data Analysts to integrate model predictions seamlessly into CRM and sales workflows.
- Stakeholder Enablement & Adoption: Translate complex technical output into actionable business insights, working directly with sales leaders to drive adoption.
- Technical Excellence: Serve as an individual contributor and technical reference point for modeling—setting best-practice standards for model architecture, validation, and productionization.
What You Bring
Must-Have
- 5+ years of dedicated Data Science experience, with a proven track record of bringing predictive models into production and measuring commercial business impact.
- Advanced proficiency in Python and SQL for handling both large structured and unstructured datasets.
- Strong background in statistical modeling, machine learning algorithms, and rigorous model evaluation protocols.
- Direct experience building at least one of the following: Customer Lifetime Value (CLV), churn prediction, lead scoring, or propensity models.
- Excellent ability to translate complex technical output into clear executive strategies and partner effectively with engineers and business stakeholders.
Nice-to-Have Qualifications
- Hands-on experience with Google Cloud Platform (BigQuery, Vertex AI, Cloud Functions).
- Expertise in A/B testing methodology, uplift modeling, and causal analysis.
- Experience integrating model outputs with Salesforce or similar CRM environments.
- Experience deploying Large Language Models (LLMs) for unstructured text and sentiment analysis.
What We Offer
- Competitive Salary + Performance-based discretionary bonus.
- Other Benefits: Private health insurance, flexible remuneration, and a day off on your birthday.
- Career Progression: A well-structured career path with clear opportunities for growth.
- Vibrant Culture: Join a collaborative environment in our Madrid office where Data Engineers, Data Scientists, Analytics Engineers, and Analysts work as one.
- Continuous Learning: Personal development through certifications and specialized training.
#LI-JC1
#LI-HYBRID
About us
Ebury delivers sophisticated, integrated solutions — business accounts, hedging, and financing — on a single platform with a seamless workflow. Our success is built on a simple premise and singular purpose: To help businesses operate and scale globally.
Since its founding in 2009, Ebury has always been a fast-growing leader in fintech. Today, we bring together 2000+ Eburians across nearly 70 cities and we’re always looking to add to our team.
At the heart of our offering is a proprietary platform, purpose-built to help businesses seamlessly streamline and manage global cash flow. We focus on continuous product evolution and innovation to build the infrastructure for borderless growth and help our clients scale at every stage.
The opportunities at Ebury are as diverse as our people, ranging from business development to engineering roles across our tech pillars.
We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.
Important Security Notice for Job Applicants:
Ebury only accepts applications via official Ebury channels. We will only contact you from an @ebury.com domain. Always check the emails you receive from us, and note that we will never request payment for any part of the recruitment process. Stay safe and report suspicious activity.
Notice to Recruitment Agencies and Search Firms:
Ebury does not accept unsolicited resumes, CVs, or candidate profiles from recruitment agencies or search firms without signed written Ebury recruitment terms in place for a specific role. Any unsolicited applications will be considered the sole property of Ebury. Ebury will not be responsible or liable for any placement fees or costs associated with unagreed candidate submissions or subsequent hires.
AI Transparency Statement:
Ebury uses Artificial Intelligence (AI) and automated tools to help streamline certain parts of our recruitment process, however, these tools are strictly for administrative efficiency. All hiring decisions, including application reviews, shortlisting, and final selections are evaluated and conducted by human talent acquisition professionals and hiring managers.
How we rate this
Senior Data Scientist at Ebury rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $166k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- Walk me through how you've used Vertex AI in your day-to-day work.
- This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
- Tell me about a time an AI tool got something wrong. How did you catch it?
Adapt your resume
- List these exact terms on your resume: AI Evaluation and Vertex AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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