Data Scientist – AI & Data Science Team

Data Scientist – AI & Data Science Team (TEB Arf, İstanbul – BÜDOTEK Teknopark)

Join TEB Arf’s innovative AI & Data Science Team and help us redefine the future of banking! We’re a dynamic group pushing the boundaries of artificial intelligence to develop cutting-edge solutions that deliver real impact. As a Data Scientist, you’ll own the entire lifecycle of AI/ML solutions – from development and deployment to monitoring and continuous improvement – collaborating closely with business stakeholders to solve complex challenges.

Key Responsibilities:

• Data Engineering & Preparation: Extract, clean, transform, and validate data from diverse sources to create high-quality datasets for model development. Design and maintain scalable data pipelines using SQL and Python.
• Model Development & Evaluation: Select, build, train, and rigorously evaluate machine learning models (regression, classification, clustering, time series) using libraries such as Scikit-learn, XGBoost, and TensorFlow/PyTorch. Employ techniques like cross-validation to ensure robust and generalizable results.
• Business Translation & Impact: Collaborate with stakeholders to understand business needs and translate them into actionable analytical solutions. Design and execute experiments (A/B testing) to validate hypotheses and measure the impact of your work.
• Deployment & Monitoring: Work with SDLC teams to deploy models into production, continuously monitor performance, and proactively address issues (model drift, data quality).
• Communication & Documentation: Clearly communicate complex technical concepts to both technical and non-technical audiences. Maintain thorough documentation of all analytical processes and results.

Qualifications:

• Bachelor’s degree in Computer Engineering, Electrical/Electronics Engineering, Industrial Engineering, Statistics, or Mathematics.
• 5+ years of experience, with at least 3 years in a dedicated Data Science role.
• Expert proficiency in SQL and Python.
• Strong understanding of machine learning/deep learning concepts, algorithms, and a practical ability to apply them.
• Hands-on experience developing and deploying machine learning models and AI applications.
• Solid understanding of MLOps and LLMOps principles.
• Familiarity with CI/CD platforms and containerization (Docker, Kubernetes).
• Excellent English communication skills (verbal and written).

Bonus Points:

• Experience with Java or C++.
• Knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI architectures.
• Master’s or PhD in a related field.
• Experience in the banking or financial services industry.