The Machine Learning Engineer plays a vital role in designing and implementing advanced models and infrastructure that drive quantitative research and trading strategies. This position focuses on building scalable systems for data ingestion, risk modeling, and back testing, while collaborating closely with traders and analysts to enhance decision-making. Key Responsibilities Architect and maintain research infrastructure for data access, risk modeling, and backtesting. Develop and refine machine learning models (e.g., Neural Networks, Random Forest, XGBoost) for predictive analytics and anomaly detection. Automate reporting and analytics dashboards using Python, Tableau, and SQL. Conduct exploratory data analysis on large financial datasets from Bloomberg, Reuters, and other sources. Collaborate with trading teams to integrate ML‑driven insights into execution strategies. Stay current with emerging ML techniques and financial technologies. Qualifications Education and Certification Master’s degree in applied Analytics or related quantitative discipline. 2+ years in ML engineering or quantitative research; exposure to financial markets preferred. Technical Skills Data visualization tools (Tableau, Matplotlib) Familiarity with cloud platforms (AWS/Azure) and version control (Git) Core Competencies Strong understanding of statistics, probability, and financial instruments (ETFs, derivatives). Ability to manage multiple projects in a fast‑paced environment. Seniority Level Entry level Employment Type Full‑time Job Function Engineering and Information Technology Industries IT Services and IT Consulting #J-18808-Ljbffr
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