Data Scientist

Enhance predictive accuracy and model robustness using gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost).,Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions.,Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.,Establish best practices for model development, validation, deployment, and monitoring in production environments.,Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.,Communicate project progress, insights, and results to stakeholders.,Design, implement, and optimize classic machine learning models to solve complex business problems.

Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Data Science, or related field; a PhD is an advantage.,5+ years of experience in data science roles.,Proven expertise in classic machine learning algorithms and techniques, including regression, classification, clustering, and feature engineering.,Extensive hands-on experience with gradient boosting frameworks such as XGBoost, LightGBM, and CatBoost.,Demonstrated success in designing, deploying, and scaling Generative AI applications (e.g., LLMs) in real-world scenarios.,Strong programming skills in Python and proficiency with data science libraries (scikit-learn, pandas, NumPy, TensorFlow, PyTorch).,Experience with cloud platforms (AWS, Azure) and MLOps tools for model deployment and monitoring in production.,Knowledge and experience in Databricks and Spark.,Ability to thrive in a fast-paced, collaborative, and innovative environment.,Experience in handling big data of billions of observations.,Knowledge of data engineering and pipeline development (preferred).,Prior experience in fintech or the payments industry is a plus (preferred).

Bachelor's Degree