ML Engineer

Responsibilities Collect, clean, and analyze large amounts of market data and financial news to identify patterns that can inform trading decisions. Develop and implement machine learning models that predict stock movements and market trends, continuously refining them to improve accuracy and profitability. Work closely with the trading team to translate model outputs into actionable trading strategies. Design and execute back-testing procedures to validate the effectiveness of trading strategies under various market conditions. Prepare reports on model performance, market analysis, and trading outcomes, providing insights and recommendations to senior management. Collaborate with software engineers and financial analysts to enhance data collection and model implementation techniques. Stay updated with the latest developments in quantitative finance, machine learning applications in trading, and financial markets to continually refine and evolve trading strategies. Qualifications Bachelor’s degree in finance, Economics, Computer Science, Data Science, Statistics, or a related field. 2+ years of experience in quantitative finance, preferably in a trading environment, with a proven track record of developing predictive models. Technical Skills: Proficient in programming languages such as Python, R, or MATLAB. Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, Keras). Strong statistical analysis and mathematical skills. Solid understanding of financial markets, instruments, and algorithmic trading systems. Exceptional analytical and quantitative problem-solving skills. Excellent verbal and written communication skills, with the ability to explain complex models and strategies to non-experts. Desirable Skills: Experience with natural language processing (NLP) to analyze financial news. Knowledge of high-frequency trading algorithms.