Data Scientist
2 semanas atrás
About the team: Our team is responsible for building behavioral-based models and engaging in research-oriented projects towards evolutionary expert systems. We see data science as a blend of science and craftsmanship—delivering solutions that exceed customer expectations. Collaboration is at the core of our team culture. Together, we embrace challenges, learn from failures, and celebrate successes. You will be joining a team that focuses on developing fraud detection models based on user and entity behavior patterns in the data. We work in a high-paced environment where projects range from evolutionary computation, llms to graph neural networks (GNNs) and machine learning research.
About the role: As a Data Scientist, you will focus on building, training, and optimizing machine learning models to solve business problems such as fraud detection. You will be involved in every stage of the data science workflow, from exploratory data analysis and feature engineering to model deployment and post-production monitoring. You will work on research-driven projects, applying the latest advancements in machine learning and AI to develop state-of-the-art solutions for complex problems. If you are passionate about data, algorithms, and applying research into real-world scenarios, this is the role for you. We thrive on solving hard problems, and we welcome those who bring innovation and fresh ideas to our team.
What do we need
- Experience in building and deploying machine learning models.
- Proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch).
- Ability to work with LLMs
- Experience with cloud-based environments like GCP
- Experience in using data pipelines for model training and inference.
- Knowledge of statistical techniques and model evaluation metrics.
- Experience working on projects related to fraud detection, risk analysis in financial services
- Experience with LLMs , Graph Neural Networks (GNNs) or other advanced deep learning architectures.
- Experience in developing scalable data science solutions for real-time applications.
- Knowledge of Google Cloud Platform (GCP) services for machine learning and model deployment.
- Design, develop, and deploy machine learning models for fraud detection and behavioral analysis.
- Collaborate with cross-functional teams, including data engineers, product managers, and software engineers, to integrate models into production.
- Research and implement new machine learning algorithms and techniques that push the boundaries of existing models.
- Monitor the performance of models in production, optimizing them for scalability and efficiency.
- Stay up-to-date with the latest trends in machine learning and data science to continuously drive innovation within the team.
- Online/take-home technical assessment
- Technical interview
- Panel interview
- Final interview
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