We are seeking a hands-on data scientist to help us build out data science model, which will be used for prediction model.
The role will involve taking ownership of the data modeling, setup of deployment-related to data modeling, building new systems where required and importantly preparing our systems and processes for anticipated massive scale in the year ahead.
At a high-level, responsibilities will extend to:
- Working with data engineers to setup and optimize our MLOps infrastructure
- The ability to work both with technical teams including product, engineering and BI/analytics as well as non-technical financial teams from fraud, risk, and compliance is essential.
- Build predictive models in conjunction with company's direction
On a day-to-day basis, responsibilities include:
- Collaborating with the team and various stakeholders to identify technical problems, design solutions for them and help implement where required. This involves collaborating with both technical and non-technical staff
- Maintain and regularly enhanced pipeline of MLOps
- Work on increasing the accuracy of the predictive model
Experience with following is required:
- Java and Python
- Kubernetes
- Kubeflow
- Airflow
- PostgreSQL
- Kafka
- Writing detailed design documents and holding design meetings
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