Data Scientist

Role Description

• Build, validate, and deploy statistical and machine learning models (e.g. anomaly detection, fraud detection, clustering, NLP, generative AI).
• Experiment with advanced techniques (e.g. graph neural networks, LLMs, deep learning) to push the boundaries of what data can deliver.
• Collaborate with engineering, product, and business teams to translate strategic questions into data-driven solutions.
• Contribute to architectural discussions on scalable, production-ready ML systems.
• Share your knowledge with a team of passionate engineers and help foster a culture of agile, data-driven decision-making.
• Use your excellent English skills to communicate daily, both verbally and in writing, in cross-functional teams.

Qualifications

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL.
• Proven experience in Data Science, Data Analysis, or related roles.
• Solid foundation in statistics, data modeling, and applied machine learning.
• Hands-on experience with cloud platforms (AWS preferred: SageMaker, Lambda, RDS, S3).
• Ability to communicate insights clearly to both technical and non-technical stakeholders.
• Experience with version control (Git) and modern development practices.
• Excellent English communication.

Requirements

• Background in scientific research or advanced studies (MSc/PhD in a quantitative field).
• Experience with LLMs (e.g. GPT, LangChain, Whisper, vector databases) or graph neural networks.
• Proficiency with full-stack or API development (FastAPI, Next.js, etc.) to deliver data products.
• Familiarity with big data tools (Spark, BigQuery, Redshift).
• Exposure to fraud detection, anomaly detection, or other high-impact ML use cases.
• Knowledge of efficient compiled languages (C++, Rust, Scala) for numerical computation.