Sr Data Scientist

Description

Senior Data Scientist, Financial Crime

About The Role

We are looking for an experienced Senior Data Scientist to join our Financial Crime (FinCrime) team.

In this role, you will apply machine learning, advanced analytics, and anomaly detection to help identify and prevent fraudulent and suspicious activity across our global financial network.

Role

You will work closely with cross-functional teams to translate complex business challenges into scalable, data-driven solutions. This is a hands-on role where you will:

• Build, test, and deploy machine learning models.
• Analyze large and complex transactional datasets.
• Develop scalable data and feature-engineering pipelines.
• Integrate ML solutions into production environments.
• Measure model performance and real-world business impact.
• Help strengthen fraud detection and financial crime prevention capabilities.

What You'll Do

• Develop Machine Learning Solutions: Design, build, test, and deploy ML models focused on anomaly detection, fraud prevention, and suspicious transactional patterns.
• Build with Python: Develop prototypes and production-ready solutions using Python and modern machine learning frameworks.
• Productionize ML Models: Move models beyond experimentation by integrating them into production environments, monitoring performance, and measuring effectiveness.
• Develop Data Pipelines: Build scalable ETL, data-processing, and feature-engineering pipelines that transform raw data into reliable inputs for ML models.
• Work in the Cloud: Develop and deploy data and ML solutions using cloud platforms such as AWS, Azure, or GCP.
• Explore Complex Data: Analyze large transactional datasets to identify patterns, correlations, anomalies, emerging risks, and potential fraudulent activity.
• Measure Business Impact: Define meaningful KPIs and evaluate model performance to ensure solutions deliver measurable business outcomes.
• Communicate Insights: Translate complex technical findings into clear, actionable recommendations for both technical and non-technical stakeholders, including senior leadership.
• Solve Complex Problems: Break down ambiguous or large-scale business challenges into manageable analytical problems and deliver solutions iteratively.
• Drive Innovation: Stay current with developments in machine learning, anomaly detection, data engineering, cloud technologies, and emerging AI capabilities.

What We're Looking For

Experience

• 4 - 5+ years of experience in Data Science, Machine Learning, or a related field.
• Demonstrated experience building, deploying, and monitoring machine learning models in production environments.
• Experience working with large, complex datasets and developing solutions that generate measurable business impact.
• Experience applying machine learning to anomaly detection, fraud detection, financial crime, payments, banking, or fintech is highly desirable.
• Experience partnering with technical and business stakeholders to translate business requirements into data-driven solutions.

Technical Skills

• Strong hands-on proficiency in Python.
• Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of machine learning modeling, anomaly detection, and model evaluation techniques.
• Experience developing ETL pipelines, data-processing workflows, and ML features.
• Experience integrating ML models and data pipelines with production or enterprise systems.
• Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
• Strong ability to analyze, visualize, interpret, and communicate insights from complex datasets.

What Will Help You Succeed

• Strong analytical, problem-solving, and critical-thinking skills.
• Ability to connect technical solutions with real business challenges.
• Excellent communication and cross-functional collaboration skills.
• Ability to explain complex technical concepts clearly to non-technical stakeholders and senior leadership.
• Comfortable working in a fast-paced environment and managing multiple priorities.
• Proactive, curious, and comfortable working with ambiguity.
• Strong interest in emerging AI, machine learning, and financial crime prevention technologies.

Benefits in Brazil

For Employees Based In Brazil, Benefits Include

• 30 days of vacation per year
• Health, dental, oncological, and life insurance
• Meal allowance
• English-language learning support
• Annual salary review based on performance
• Professional development and career growth opportunities