Description:

The Data Scientist / Machine Learning Engineer at ViaBill will be responsible for advanced analytics tasks such as data analysis, statistical modeling, and machine learning.
Responsibilities include building credit decision models, fraud detection models, validating data source predictive power, and providing data-backed input for business crucial decisions.
The role also involves deploying and maintaining existing decision models and performing simple data engineering tasks like writing SQL scripts to transform raw data into features.
The position requires an understanding of practical machine learning application, from raw data transformation to model deployment and maintenance.
The role offers freedom in selecting tools and methods, with a real impact on the platform's design.
Collaboration with internal stakeholders and cross-functional teams is essential to solve problems and create operational efficiencies.
This is a full-time remote position.

Requirements:

Hands-on experience in developing machine learning models, demonstrated through previous commercial projects, portfolio at a git repository, or Kaggle competitions.
Proficiency in machine learning pipelines, data visualization, data validation, statistical testing, and presenting findings to a non-technical audience.
Preferably, relevant experience in risk management (fraud/credit), consumer lending, consumer finance, and/or business growth, but expertise in any area where classification or regression models were created is appreciated.
Understanding of machine learning techniques like logistic regression, gradient boosting algorithms, and basic neural network architecture.
Proficiency in Python and SQL for machine learning programming, knowledge of ML frameworks (scikit-learn, pandas, numpy, Keras/tf/PyTorch, matplotlib), and basic understanding of cloud tools (AWS, Google, Azure).
Self-driven with the ability to work independently, fluency in English, and familiarity with data science frameworks like Kedro or MLflow is a plus.

Opportunity to work with a highly motivated remote team of developers in a flat hierarchy with a streamlined process.
Collaboration similar to open-source projects with core maintainers for services and easy access to domain experts via Slack or Meet.
Rapid release schedule with frequent releases, providing quick feedback and visibility of the impact on the business.
Ability to experiment and adopt new trends/frameworks quickly.