Staff Data Scientist

This is a fully remote position, open to applicants anywhere in the world.

📋 Description

• Lead high-complexity ML projects by designing, implementing, and deploying critical models for credit, personalization, and fraud prevention.

• Develop methodological guides, experimentation frameworks, code quality criteria, and MLOps architectures for all Data Science teams.

• Conduct impactful code reviews, methodological audits of models, and provide technical mentoring to Senior Data Scientists and Leads.

• Anticipate technical debt and outline the adoption of new tools, cloud infrastructure, and ML/AI methodologies with a 2-3 year vision.

• Monitor papers, trends, and emerging technologies such as GenAI and causal inference.

• Establish partnerships and research projects with universities to transform cutting-edge knowledge into competitive advantage.

⛳️ Requirements

• Proven experience in Data Science, ML Engineering, or applied AI.

• At least 3 years serving as a technical reference in Staff, Principal, or Lead Technical roles.

• Documented track record of solving and implementing high-complexity ML problems at scale.

• Expert-level proficiency in Python for Machine Learning, including scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow.

• Advanced SQL and experience with BigQuery for handling large data volumes.

• Experience in designing ML architectures in production using Vertex AI, MLflow, SageMaker, or equivalent platforms.

• Expert knowledge of advanced statistics, causal inference, experimental design, and probability theory.

• Demonstrated ability to design frameworks, architectures, and technical RFCs adopted by multiple teams.

• Degree in Computer Engineering, Mathematics, Physics, Statistics, or Computer Science.

• Advanced English proficiency for reading and writing technical papers and documentation.

• Desirable: experience with LLMs, fine-tuning, RAG, or agentic AI.

• Desirable: knowledge of credit models or fraud prevention in FinTech or regulated banking.

• Desirable: experience with explainability and fairness in AI, including SHAP, LIME, or AI Act.

• Desirable: postgraduate degree, technical publications, open-source contributions, or an academic network in AI.

🏝️ Benefits

• Annual budget for self-managed training.

• Remote work options.

• Day off on your birthday.

• Half-day off for the birthdays of children or parents.

• Short Fridays (we finish at 2 PM every Friday).

• Work from anywhere (Work from wherever you want! Just remember to have a good internet connection).