Senior Data Scientist

IDT is expanding its AI Lab and seeking a hands-on, highly experienced Senior Data Scientist with a proven track record of building new ML models from scratch and deploying them into real-time production. You will tackle complex problems across fraud prevention, payment risk, transaction scoring, personalization, and financial forecasting using large-scale transactional datasets. You will own the full modeling lifecycle - from problem framing through to production monitoring.

Key Responsibilities:

• ML & Predictive Modeling: Design and build new models from the ground up (gradient boosting, neural networks, ensembles, anomaly detection) for anti-fraud, risk assessment, and personalization; maintain rigorous validation practices to prevent data leakage and overfitting.

• End-to-End & MLOps: Partner with Data Engineering and MLOps to operationalize models in production (batch and real-time/low-latency); build training, experiment tracking (MLflow), and model/data drift monitoring pipelines.

• Experimentation & Business Impact: Design A/B tests and statistical evaluations to measure model performance against key business metrics (reduced fraud losses, transaction acceptance rates, decision latency).

• R&D & Technical Leadership: Explore emerging techniques (LLMs/GenAI, graph-based methods), establish engineering best practices, and mentor fellow team members.

Requirements (Must-Have):

• Experience: 5+ years of hands-on experience in Data Science / ML, with a strong focus on designing and building new ML models from scratch and delivering them into production with measurable business impact.

• English: B2+ (Upper-Intermediate or higher) - fluent written and spoken communication for technical discussions and daily collaboration with an international team.

• Math & Modeling Foundations: Deep understanding of statistics, probability, and validation methodologies; practical experience handling class imbalance, model calibration, and anomaly detection.

• Tech Stack:

• Python: Advanced proficiency (Scikit-learn, Pandas, NumPy);

• Deep Learning: Hands-on experience with PyTorch or TensorFlow;

• SQL: Complex queries and large-scale data manipulation;

• MLOps Tools: Experiment tracking and model lifecycle management (MLflow, ClearML, etc.).

• Education: Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field.

Nice-to-Have:

• Domain experience in FinTech, Payments, or Fraud Prevention: real-time transaction scoring and low-latency inference.

• Experience with cloud data platforms (Snowflake), Feature Stores, and event-driven architectures.

• Background in time-series forecasting, graph neural networks, Explainable AI (XAI), or applied LLM solutions.

• Master’s degree or Ph.D. in a quantitative discipline.

We offer you:

• Remote b2b or hybrid (Belarus-Moldova) work opportunity!
• Stable job with long-term growth perspective.
• Competitive salary with annual performance review.
• Really good hardware.
• An exciting and challenging job with talented people around.
• Continuous learning and career growth opportunities.
• Compensation for professional training, seminars, and conferences.
• Referral program - get rewarded for helping us grow the team with talented people.
• Company-supported English classes to enhance your professional growth.
• More perks for the Minsk and Chisinau office employees.