Ml engineer

На данный момент Senior Software Engineer.

Мои компетенции и опыт

Ethan Lim

Singapore | нужен доступ к резюме | нужен доступ к резюме | нужен доступ к резюме

Summary

Highly skilled Machine Learning Engineer with 10+ years of professional experience in designing, developing, and deploying advanced ML models for predictive analytics and algorithmic trading. Specialized in quantitative modeling, mid- to high-frequency strategies, and portfolio optimization using Python and C++. Experienced in large-scale data analysis, pattern recognition, and backtesting pipelines for financial markets. Adept at collaborating with trading leads and cross-functional teams to translate industrial hypotheses into actionable, high-performance models. Proven record of delivering measurable gains, strategy optimization, and scalable ML solutions in remote and fast-paced environments.

Experience

Rescode | Senior Software Engineer May 2022 ~ Present

• Developed ML models to predict price dynamics and identify inefficiencies in financial markets
• Designed, implemented, and maintained pipelines for automated backtesting and model optimization
• Applied Python and C++ for high-performance modeling and strategy simulations
• Conducted feature engineering and preprocessing on large-scale market datasets
• Optimized mid-frequency and arbitrage strategies to enhance trading performance
• Performed comparative analyses on multiple ML algorithms to identify the most effective models
• Integrated predictive models with internal trading systems to support decision-making
• Implemented robust monitoring, logging, and evaluation workflows for model performance
• Built synthetic and historical datasets to validate and improve predictive strategies
• Collaborated closely with trading leads to test and validate hypotheses on real-world data
• Mentored junior engineers in ML techniques, quantitative modeling, and Python best practices
• Improved computational efficiency, reducing model training time by over 35%
• Participated in strategy design discussions and system architecture decisions
• Conducted research on emerging ML techniques to enhance prediction accuracy
• Produced detailed technical documentation and reports for team knowledge sharing
• Delivered measurable improvements in strategy efficiency and predictive accuracy

Doodle Labs | Senior Full Stack Engineer Apr 2019 ~ Apr 2022

• Designed and implemented ML models for financial time series forecasting and anomaly detection
• Built pipelines for model training, evaluation, and deployment in production environments
• Developed predictive algorithms for market trend analysis using Python and C++
• Applied reinforcement learning and quantitative modeling techniques to trading scenarios
• Conducted statistical analysis and optimization of trading strategies
• Collaborated with cross-functional teams to integrate ML models into internal systems
• Performed feature selection, preprocessing, and model tuning to maximize accuracy
• Designed backtesting frameworks to evaluate strategies under historical market conditions
• Led experiments comparing multiple ML architectures for optimal trading performance
• Mentored team members on reinforcement learning, predictive modeling, and algorithmic trading
• Implemented scalable pipelines for handling high-volume market datasets
• Improved system reliability, ensuring models met latency and performance targets
• Documented ML workflows, backtesting results, and quantitative strategies for team use

Wise | Full Stack Engineer May 2015 ~ Feb 2019

• Developed ML solutions for financial forecasting and predictive analytics
• Designed quantitative models and simulations to support portfolio and strategy decisions
• Implemented Python and C++ pipelines for time series analysis and pattern detection
• Conducted backtesting and validation of predictive trading algorithms
• Automated data preprocessing, feature extraction, and model evaluation workflows
• Collaborated with trading and analytics teams to refine ML-driven strategies
• Conducted comparative analysis of model performance and algorithmic efficiency
• Applied statistical methods to detect anomalies and optimize strategy outputs
• Mentored junior engineers in quantitative modeling, ML techniques, and Python development
• Ensured model reproducibility, scalability, and robustness in production pipelines
• Produced clear documentation of models, pipelines, and experimental results

Education

National University of Singapore Aug 2009 ~ Jul 2013

Bachelor’s Degree in Computer Science

Skills

• Programming & Data: Python, C++, Pandas, NumPy, SciPy, scikit-learn, TensorFlow, PyTorch, Reinforcement Learning, Time Series Analysis, Feature Engineering, Backtesting, Quantitative Modeling
• ML/AI: Mid-Frequency Strategies, Arbitrage, Portfolio Optimization, Predictive Modeling, Forecasting, Simulation, Pattern Recognition, Algorithmic Trading
• Cloud & DevOps: AWS, Azure, GCP, Docker, CI/CD Pipelines, Cloud-Based ML Deployment, High-Performance Computing
• Database & Big Data: SQL, PostgreSQL, NoSQL, Large-Scale Dataset Handling, Data Validation, Data Integration
• Collaboration & Tools: Agile, Scrum, Jira, Confluence, Git, Code Reviews, Mentorship, Cross-Functional Team Collaboration
• Other: Problem Solving, Analytical Thinking, Research, Experimentation, Performance Profiling, Technical Documentation