Senior Data Scientist
Team: Data & AI
Location: Madrid, Montevideo, Barcelona, Buenos Aires, Sao Paulo (Hybrid)
Commitment: Full Time
Workplace Type: hybrid
We are looking for a high-impact Senior Data Scientist with the vision and technical depth to eventually shape our data science standards. You are an elite individual contributor today, but you think like an architect. You don't just solve the problem in front of you; you build the systems, patterns, and documentation that make future problems easier to solve. You will act as a strategic partner to the business, leveraging cutting-edge AI and MLOps to solve complex problems in anomaly detection, forecasting, and payments routing that directly add value for dLocal.
What will I be doing?
- End-to-End System Ownership: You don’t just "hand over" a model. You own the design of the full ML lifecycle—from raw data sources and feature engineering to deployment, roll-out strategies, and monitoring.
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Operational Excellence: Lead or support root-cause analyses for incidents involving models or data. You use these "failures" as data points to improve our platform’s reliability and observability.
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Peer Leadership & Review: Raise the collective bar by providing constructive feedback on code, design docs, and analytical thinking for your peers. You are a natural mentor who enjoys upskilling others.
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Strategic Roadmapping: Influence the direction of the data science vertical by connecting technical breakthroughs (new models, LLMs, platform features) with high-value business opportunities in anomaly detection, routing, fraud.
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Automation & Standardization: Actively look for opportunities to turn "one-off" solutions into reusable components, templates, or standards that the entire team can leverage.
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AI-Accelerated Development: Champion the use of AI-assisted tooling (LLMs, Copilots) to maximize throughput while maintaining high code quality and architecture standards.
What skills do I need?
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Advanced Technical Execution: 6+ years of experience in ML and Statistics. You possess the mathematical depth to modify algorithm implementations and the engineering rigor to deploy them.
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MLOps & Cloud Proficiency: Solid experience with cloud-based ML (AWS/GCP/Databricks). You understand model registries, CI/CD for ML, and feature pipelines. Proven experience on Databricks is a strong plus.
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Architectural Intuition: Ability to reason about trade-offs between analytical sophistication, engineering complexity, and operational risk. You know when a simple regression is better than a complex neural network.
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Strategic Stakeholder Influence: You are an expert storyteller. You can translate technical "deep dives" into clear business value for stakeholders at all levels.
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Expert Tooling Knowledge: Strong knowledge of ensemble methods, deep learning, and hybrid time-series models. You choose the right tool (Spark, SQL, SageMaker) based on the specific scale and business challenge.
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Self-Driven Execution: Experience managing complex project roadmaps across a business vertical with sharp attention to detail.
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Industry Context: Experience in payments or financial systems (Anomaly or Fraud detection) is beneficial.
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Language: Advanced English is a must.
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