Job
Description
Develop analytical tools using SQL & Python to drive business insights Utilize outlier detection methodologies to identify data anomalies in the financial risk space, ensuring proactive risk management Analyze business requirements and translate them into practical solutions, developing data-driven controls to mitigate potential risks Plan and execute projects from concept to final implementation, demonstrating strong project management skills Present solutions to senior stakeholders, effectively communicating technical concepts and results Collaborate with internal and external auditors and regulators to ensure compliance with prescribed standards, maintaining the highest level of integrity and transparency. To be successful in this role, we re seeking the following: A Bachelors degree in Engineering, Computer Science, Data Science, or a related discipline (Masters degree preferred) At least 3 years of experience in a similar role or in Python development/data analytics Strong proficiency in Python (including data analytics, data visualization libraries) and SQL, basic knowledge of HTML and Flask. Ability to partner with technology and other stakeholders to ensure effective functional requirements, design, construction, and testing Knowledge of financial risk concepts and financial markets is strongly preferred Familiarity with outlier detection techniques (including Autoencoder method, random forest, etc.), clustering (k-means, etc.), and time series analysis (ARIMA, EWMA, GARCH, etc.) is a plus. Practical experience working with Python (Pandas, NumPy, Matplolib, Plotly, Dash, Scikit-learn, TensorFlow, Torch, Dask, Cuda) Intermediate SQL skills (including querying data, joins, table creation, and basic performance optimization techniques) Knowledge of financial risk concepts and financial markets Knowledge of outlier detection techniques, clustering, and time series analysis Strong project management skills
