Eugene Elliot L.

Proficient in Python, R, SQL, and experience with libraries such as Pandas, NumPy, and scikit-learn for data manipulation, analysis, and machine learning. Experience with supervised and unsupervised learning techniques, model selection, and tuning. Skilled in applying algorithms like decision trees, regression, clustering, and neural networks (e.g., LSTM models for sequential data). Comfortable with cleaning, transforming, and preparing raw data, identifying data quality issues, and managing large datasets. Ability to interpret complex datasets and extract meaningful insights, applying statistical methods to validate findings. Skilled in developing forecasting models and predictive analytics, particularly in finance or trading environments (e.g., predicting forex movements). Capable of creating clear, insightful visualizations using tools like Matplotlib, Seaborn, or Tableau to communicate findings to stakeholders. Hands-on experience in building end-to-end data science pipelines, from data collection and cleaning to model deployment and performance monitoring. Consulting on data-driven decision-making, predictive model development, A/B testing, and optimization strategies. Delivering actionable insights to help businesses mitigate risk and enhance their strategies. Passion for working on AI applications in finance, healthcare, and marketing; keen interest in projects involving NLP, time series forecasting, and causal inference. Strong ability to translate complex data science concepts into actionable insights for non-technical stakeholders. Experience working cross-functionally, understanding business needs, and adapting solutions accordingly.