Analyst within Credit Risk Management team identifying credit segmentation opportunities using statistical methods. Collaborating with teams to enhance credit decision process and policies.
About the role
- Design and develop reusable Python packages (pip/conda) to productionize data science solutions.
- Process big data at scale using Hadoop/Spark and optimize workflows with Airflow/orchestration tools.
- Build scalable applications and REST/RPC APIs (Flask/FastAPI/gRPC) for global products.
- Advocate for engineering best practices, including CI/CD, DevOps, and containerization (Docker/Kubernetes).
- Mentor junior engineers and lead initiatives to enhance research tooling and dashboards.
Requirements
- At least 5-6 years of relevant experience as a data scientists applying analytics, data science or operational research skills at scale
- Numerate degree with large amount of the content covering data science, advanced analytics and/or operational research
- 7+ years in data engineering/science, with expertise in Python, Spark, and SQL.
- Proven experience with big data processing and scalable system design.
- Strong knowledge of CI/CD, Agile frameworks, and cloud platforms (AWS).
- Bonus: Familiarity with ML techniques (regression, clustering) and retail data.
Benefits
- The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
- The opportunity to form part of an amazing, multicultural community of tech experts.
- A highly competitive compensation package.
- Medical insurance.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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