Machine Learning Engineer Intern

About the role

Join the projectB2H team to help build a Sharia‑compliant trading assistant that analyses financial markets and generates BUY / HOLD / AVOID signals with explanations. You will work alongside two other interns to deliver a minimum viable product in one month.

Key responsibilities

• Collect and prepare historical market datasets for model training.
• Clean, preprocess and engineer features from technical indicators, candlestick patterns and price‑action data.
• Develop and compare machine‑learning models such as logistic regression, Random Forest, XGBoost, LightGBM and optionally LSTM.
• Evaluate models using accuracy, precision, recall, F1‑score, confusion matrix and back‑testing metrics (win rate, risk/reward, maximum drawdown).
• Deliver a financial data pipeline, feature‑engineering module, trained models, evaluation report and back‑testing results.

Required profile

• Currently studying data science, statistics, computer science or a related field.
• Understanding of evaluation metrics and the risk of over‑fitting on financial time series.
• Methodological honesty about data leakage and model validity.
• Interest in financial markets is a plus, but not mandatory.

Required skills

• Python programming.
• Data‑science libraries such as pandas and scikit‑learn.