Full Stack Data Scientist

Topaz

Full Stack Data Scientist at Topaz analyzing structured and unstructured data for fraud detection. Developing machine learning models and maintaining automated pipelines in a hybrid working environment.

Posted 6/1/2026full-timeIndaiatuba • 🇧🇷 BrazilMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSDockerDynamoDBEC2GrafanaKerasKubernetesMongoDBNoSQLNumpyOpen SourcePandasPythonPyTorchSQLTensorflowTerraform

About the role

Key responsibilities & impact

Analyze structured and unstructured data to identify patterns of fraud and money laundering
Develop machine learning models (classification, clustering, anomaly detection) for financial security problems
Apply feature engineering, handle missing values, normalize data and balance datasets
Prevent data leakage when splitting and validating datasets
Create visualizations to communicate results to different audiences
Experiment with various algorithms (Scikit-Learn, LightGBM, CatBoost, Keras, TensorFlow, PyTorch)
Work with distributed data stores (Athena, Hive) processing large volumes
Optimize SQL queries to reduce cost and execution time
Handle structured data (CSV, Parquet) and unstructured data (JSON, images)
Develop data transformation and preparation pipelines
Create and maintain automated ML pipelines (training, validation, deployment)
Containerize applications with Docker
Manage pods and deployments with Kubernetes
Ensure scalability and availability of solutions
Monitor model performance in production
Detect and remediate data drift and concept drift
Configure alerts and metric dashboards (Grafana or similar)
Implement automated retraining and model versioning
Apply explainability techniques (XAI) for regulatory compliance
Research new technologies and ML algorithms
Contribute to best practices and technical documentation
Stay up to date in Data Science and Machine Learning

Requirements

What you’ll need

5+ years in software development
3+ years in Data Science and/or Machine Learning Engineering
Strong knowledge of mathematics, statistics, and probability
Experience with classification, clustering, and anomaly detection algorithms
Mastery of the full ML lifecycle: transformation, feature engineering, training, validation
Frameworks: Scikit-Learn, LightGBM, CatBoost, Keras, TensorFlow, PyTorch
Proficiency with NumPy and Pandas
Unstructured data (JSON, images)
Visualization (Matplotlib, Seaborn, Plotly, ApexCharts)
Experience with SQL and relational databases
NoSQL (MongoDB, DocumentDB, DynamoDB)
Distributed data stores (Athena, Hive)
Query optimization
ORM in Python
Robust Python development
Git for version control
DVC for data and model versioning
venv/virtualenv for Python environment management
Data structures, algorithms and design patterns
Testing: pytest (unit), Locust (load)
S3, Athena, DynamoDB, EC2, Lambda, ECR, ECS/EKS
Docker for containerization
Kubernetes for orchestration
Terraform (basic concepts)
GitLab CI/CD (basic concepts)
Differentials: MLOps tools: MLflow, Kubeflow, Metaflow
Data pipeline orchestration: Dagster (desirable)
Feature stores and model registry
Experience in fraud detection, anomaly detection or financial security
NLP or image processing (OpenCV, PIL)
FastAPI to expose models as a service
AWS certifications (Solutions Architect, ML Specialty)
Open source contributions or technical publications
Autonomy for end-to-end projects
Clear communication (technical and non-technical)
Analytical, results-oriented mindset
Proactivity and innovative spirit
Collaboration with multidisciplinary teams
Genuine interest in fraud, risk and financial security domains

Benefits

Comp & perks

🌱 Integrated Well‑being: Your well‑being is fundamental. We take care of you and your loved ones with comprehensive health plans, because a healthy team is a team that transforms.
🚀 Development and Growth: Your career doesn't stop. At Topaz, #Evolution is constant. Through training programs and daily challenges, we provide the tools so your potential has no limits.
⚖️ Flexibility and Balance: We believe in balance. Enjoy the flexibility you need to perform at your best with our hybrid working model and a day off on your birthday to celebrate as you deserve.

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningclassificationclusteringanomaly detectionfeature engineeringdata transformationdata preparationquery optimizationdata structuresalgorithms

Soft Skills

clear communicationanalytical mindsetresults-orientedproactivityinnovationcollaborationautonomytechnical documentationbest practicesresearch

Certifications

AWS Solutions ArchitectAWS ML Specialty