Data Scientist

Türkiye·İstanbulFull-Timemid

Data ScientistData

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Quick Summary

Overview

At Midas, we are working on real-life user needs to transform the world of finance. We’ve transformed investing in Turkey by delivering a seamless experience for everyday investors. Today, 4 million users invest with Midas.

Technical Tools

pythonsqlfintechmachine-learningstatistical-modeling

At Midas, we are working on real-life user needs to transform the world of finance.

We’ve transformed investing in Turkey by delivering a seamless experience for everyday investors.

Today, 4 million users invest with Midas. Backed by an $80M Series B, the largest fintech investment ever in Turkey, we are scaling faster than ever.

Understand business objectives and data requirements, translating them into actionable insights and predictive or generative solutions.

Develop, evaluate, and productionize machine learning and generative AI solutions (e.g., personalization, ranking, fraud detection, LLM-powered features).

Apply modern approaches (LLMs, retrieval systems, embeddings, agents) to improve tagging, monitoring, and user-facing experiences.

Testing, Evaluation & Benchmarking – own experiment design, metric definition, and continuous assessment of predictive or generative pipelines.

Taxonomy Management – create and maintain hierarchical label and eval schemes for text classification/generation projects.

Work with large datasets to summarize and extract key insights, providing valuable information to support business strategies.

Collaborate with business partners and departments to ensure data-driven solutions align with business goals and deliver optimal results.

Takes full ownership — doesn’t wait, just solves

Questions assumptions and rebuilds from first principles

Balances speed and quality — ships fast, but always clean

Collaborates fluidly across teams; communicates clearly, with empathy and precision

Bachelor’s degree in Mathematics, Physics, Engineering and relevant fields.

Knowledge and hands-on experience using SQL, Python, Python DS/ML Stack.

Experience in manipulating large datasets, summarizing key insights, and applying statistical analysis or data mining techniques to uncover patterns and answer business questions.

Generative AI adoption to scale tagging, monitoring, analytical and agentic pipelines.

Track record of impact in product facing roles.

Search and retrieval background.