Data Scientist

Role Overview

A Data Scientist builds and optimizes data‑driven solutions by developing machine learning models and maintaining end‑to‑end data science platforms, including feature engineering, model training, deployment, and monitoring. The role also involves improving technical frameworks, conducting data analysis (especially for credit scoring), and researching methodologies to enhance model performance.

• Develop and maintain the fundamental platforms for the data science team, including feature engineering, model training, and model monitoring.
• Upgrade and refactor the basic technical frameworks within the team, covering model serving, code management, and other related infrastructure.
• Assist other data scientists in resolving technical issues related to model deployment and decommissioning.
• Research model methodology and data mining techniques to improve model performance.
• Conduct data analysis and credit modeling tasks, ensuring the performance of modeling results.

• Bachelor’s degree in Computer Science, Data Science, Statistics, or related fields.
• Minimum 3 years of experience in Machine Learning Engineering, MLOps, or related areas.
• Strong Python skills for automation, pipelines, and tooling; familiar with Linux and database design.
• Experience in ML platform development, including feature engineering, model training, evaluation, deployment, and monitoring.
• Hands‑on experience with REST APIs, Docker, Kubernetes, workflow orchestration tools (Airflow, Prefect), and Git.
• Familiar with MLOps practices such as model versioning, lineage, reproducibility, and observability.
• Solid understanding of ML/DL algorithms (logistic regression, decision trees, random forests, neural networks).
• Experience in financial credit scoring models is mandatory.
• Comfortable working in regulated or data‑sensitive environments.
• Good English communication skills and able to collaborate across teams.
• Experience in AI Agent implementation is a plus.

• Experience with feature stores, CI/CD, Terraform, or Helm.
• Familiarity with risk models, financial data products, or model risk frameworks (e.g. SR 11‑7).
• Background in statistical modeling or ML experimentation.

• Innovative Environment:
  Continuously investing in cutting‑edge technologies, including artificial intelligence, your role becomes a pivotal part of our journey into the dynamic and evolving landscape of financial services. Being part of our innovative environment is your gateway to an exciting and forward‑thinking career.
• Impactful Work:
  We offer more than just a job; we provide an opportunity to play a crucial role in shaping the financial future of individuals and businesses across the nation. As a licensed credit bureau, our commitment to accuracy, reliability, and timeliness sets the stage for impactful work.
• Professional Development:
  We are committed to the growth of our employees. Join a team that encourages continuous learning and offers opportunities for career advancement.
• Collaborative Culture:
  Work in a collaborative and inclusive environment where your ideas are valued, and teamwork is key to achieving our goals.