Data Scientist

Overview In this Data Scientist role, you will advance ML models and estimators to boost payment performance across a merchant portfolio. You'll collaborate with data scientists, product, and engineering to enhance core offerings, safeguard customer lifetime value, and ensure safe model launches with strong observability.

You'll design experiments to prevent data leakage, evaluate models robustly, and productionise features and models. You will write clean, production-grade Python code and clearly communicate findings to technical and non-technical stakeholders.

This role offers a chance to impact scaling and reliability in a fast-paced fintech environment. Responsibilities Research and develop new ML models and estimators to improve Acceptance Rate. Design experiments with focus on time-based data leakage and robust evaluation.

Collaborate to productionise ML features and evolve evaluation/monitoring frameworks. Write clean, interpretable Python code for feature Engineering and model training. Communicate hypotheses, evaluation results, and dashboards to diverse audiences.

Key requirements 3+ years of experience building ML models for business problems. Strong knowledge of supervised ML algorithms, tuning, and evaluation. Experience with feature engineering techniques (e.g., target encoding).

Solid understanding of frequentist and Bayesian statistics for estimation and experimentation. Proficient in production-grade Python for training and inference. Interest in leveraging LLMs to boost coding and process productivity. strong communication (clear hypothesis and results) collaboration with cross-functional teams curiosity and problem-solving mindset Machine learning modeling Feature engineering Python production code (training and inference)

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