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Quantitative AI Developer
Location: İstanbul / Ankara
Work Model: Hybrid
About the Role
We are supporting one of our client companies in their search for a Quantitative AI Developer.
The selected candidate will be responsible for building and maintaining AI and machine learning models that power the company’s analytical and trading infrastructure. You will apply advanced statistical and computational methods to large-scale market and operational datasets, designing predictive systems that enhance forecasting, risk analysis, and portfolio performance.
This is a highly technical and research-oriented role ideal for candidates with strong AI/ML modeling experience who are eager to see their models make a direct market impact in global commerce.
Responsibilities
• Build advanced models leveraging large-scale and complex datasets to generate predictive insights for derivative products.
• Design, train, and test quantitative and machine learning models to identify predictive signals from time series and alternative data sources.
• Conduct in-depth quantitative and qualitative assessments of model performance, including theoretical soundness, design integrity, implementation quality, and data consistency.
• Research and implement machine learning algorithms to support forecasting and trading strategy development across derivative products and related markets.
• Develop software features and automation tools that enhance scalability, reliability, and efficiency.
• Build and maintain APIs, services, and back-end tools to integrate models into production environments.
• Collaborate closely with cross-functional teams to ensure scalable, accurate, and efficient model deployment.
Requirements
• Bachelor’s or Master’s degree in Computer Engineering, Software Engineering, or a related discipline.
• Minimum 2 years of experience in a Quantitative Developer, AI Developer, or similar analytical role.
• Strong programming skills in Python (pandas, NumPy, scikit-learn, PyTorch, etc.).
• Solid understanding of statistics, econometrics, and machine learning principles.
• Experience in developing and maintaining production-level ML systems or analytical tools.
• Familiarity with time series modeling (ARIMA, XGBoost, LSTM, etc.) is a plus.
Preferred Qualifications
• Experience with machine learning or deep learning applications for financial data.
• Familiarity with big data and cloud environments (e.g., Spark, AWS, GCP).
• Experience with financial data APIs (Bloomberg, Refinitiv, yFinance, etc.).
• Relevant certifications such as CFA, FRM, or formal training in Quantitative Finance.
Soft Skills
• Ability to communicate complex quantitative and financial concepts clearly to non-technical stakeholders.
• Strong collaboration and coordination skills across technical and business teams.
• Proactive, solution-oriented, and adaptable in fast-changing market environments.
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