As a Data Scientist II at Klivvr, you’ll play a key role in developing, optimizing, and deploying data-driven solutions that power our products and drive business decisions. You’ll work closely with cross-functional teams including Product, Engineering, Marketing, and Risk to deliver actionable insights and predictive models that shape the future of fintech in the region.
What you'll do:
Design and implement advanced statistical models and machine learning algorithms for customer segmentation, credit scoring, fraud detection, and more.
Translate business problems into analytical solutions with measurable impact.
Collaborate with data engineers to productionize and scale models using best-in-class tools and infrastructure.
Analyze user behavior and transactional data to identify trends, patterns, and opportunities.
Present insights and recommendations clearly to non-technical stakeholders.
Continuously improve model performance and maintain model health post-deployment.
Contribute to the development of internal data science frameworks, tooling, and best practices.
To succeed in this role, you'll need to have:
2+ years of hands-on experience in data science or applied machine learning roles.
Strong proficiency in Python (NumPy, pandas, scikit-learn, etc.) and SQL.
Solid understanding of statistics, probability, and machine learning algorithms.
Experience working with large-scale datasets and cloud platforms.
Comfortable with version control tools (Git) and collaborative development workflows.
Strong communication skills and the ability to work cross-functionally.
Preferrable to have:
Experience in fintech or consumer finance domains.
Familiarity with MLOps tools (e.g., MLflow, Airflow, Docker).
Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
Experience with BI tools like Looker, Tableau, or Power BI.
