20 publicaciones de empleo destacadas de data scientist python en madrid, md (¡Están contratando!)

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Expedia —Madrid, Madrid provincia
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Data Specialist for Compliance — Transaction Monitoring & Financial Crime

dLocal -
Madrid, Madrid provincia

Solicitud rápida

Detalles del empleo

Jornada completa
Hace 4 horas

Cualificaciones

Informática
Máster
SQL
Gestión de compliance
Grado
Python

Descripción completa del empleo

Why should you join dLocal?

dLocal enables the biggest companies in the world to collect payments in 40 countries in emerging markets. Global brands rely on us to increase conversion rates and simplify payment expansion effortlessly. As both a payments processor and a merchant of record where we operate, we make it possible for our merchants to make inroads into the world’s fastest-growing, emerging markets.

By joining us you will be a part of an amazing global team that makes it all happen. Being a part of dLocal means working with 1000+ teammates from 30+ different nationalities and developing an international career that impacts millions of people’s daily lives. We are builders, we never run from a challenge, we are customer-centric, and if this sounds like you, we know you will thrive in our team.

What's the opportunity?

We're looking for a seasoned Data Specialist with at least 5 years of experience to join our Compliance team, focused on Anti-Money Laundering (AML) and Countering the Financing of Terrorism (CFT) transaction monitoring. You'll own the analytical backbone of our transaction monitoring systems, and actively build the broader data strategy work within Compliance — whether through liaising with a team of data scientists or through influencing Product teams working upstream to us. This is a hands-on role with real influence on how we detect financial crime across LATAM, EMEA, and APAC.

What will you be doing?

Own the end-to-end analytical lifecycle of our rule-based transaction monitoring systems, from data pulling and exploration in Databricks to proposing rule and threshold changes in alignment with Compliance Leadership requirements.
Maintain and refine our false negative methodology — how we identify what monitoring is missing, not just what it catches.
Help shape the agentic monitoring function — from orchestration design to implementation — as we expand automation across our AML/CFT monitoring flows.
Act as the technical liaison with data scientists for ML driven detection: gather and document requirements, challenge and validate models delivered, and ensure outputs are usable for compliance decision-making.
Own regulatory reporting for AML/CFT transaction monitoring, ensuring the underlying data is accurate, complete, and traceable — proactively identifying and resolving data quality issues before they become reporting or audit problems.
Build and maintain audit-ready documentation for every methodology change — rationale that can be defended to a regulator or auditor months after the decision was made, by someone who wasn't in the room.
Engage with Compliance Leadership to translate evolving AML/CFT regulatory requirements into concrete data and monitoring needs.
Generate reports and dashboards that communicate overall Framework performance and monitoring effectiveness to both technical and non-technical stakeholders.

What skills do you need?

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or proven experience in a correlated field.
5+ years of experience in data analytics, risk, or fraud/financial crime analytics, ideally in financial services or fintech. Deep AML/CFT transaction monitoring experience is a strong plus but not mandatory.
Strong SQL and Python (Databricks environment preferred); comfort with statistical analysis — this is not exclusively a data scientist role, so ML frameworks are a plus, not a requirement.
Solid understanding of the end-to-end data lifecycle — from raw data and pipelines to modeling and reporting — enough to collaborate effectively with Data Engineers, Data Analysts, and Data Scientists.
Demonstrated experience as a technical liaison or requirement-owner working with additional Data, Product and Engineering teams — someone who can push back on a delivery that doesn't meet the need, not just accept what's handed over.
Experience producing documentation that holds up under audit or regulatory scrutiny is a strong plus.
Proactive, collaborative mindset; comfortable operating with a high degree of autonomy on AML data analytics, as part of a small and growing team.

What do we offer?

Besides the tailored benefits we have for each country, dLocal will help you thrive and go that extra mile by offering you:

Flexibility: we have flexible schedules and we are driven by performance.

Fintech industry: work in a dynamic and ever-evolving environment, with plenty to build and boost your creativity.

- Referral bonus program: our internal talents are the best recruiters - refer someone ideal for a role and get rewarded.

Social budget: you'll get a monthly budget to chill out with your team (in person or remotely) and deepen your connections!

dLocal Houses: want to rent a house to spend one week anywhere in the world coworking with your team? We’ve got your back!

Flexibility in how you work: We focus on impact and productivity over fixed hours. This means our teams have flexible schedules and, depending on your role and location, you will combine self‑managed focus time with moments of in‑person connection in our collaboration hubs.

What happens after you apply?

Our Talent Acquisition team is invested in creating the best candidate experience possible, so don’t worry, you will definitely hear from us. We will review your CV and keep you posted by email at every step of the process!

Also, you can check out our webpage, Linkedin and Youtube for more about dLocal!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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