Data Scientist

Responsibilities:

• Assist in developing and training machine learning models for credit scoring, fraud detection, and risk prediction.
• Perform data cleaning, preprocessing, and feature engineering on large datasets.
• Support model evaluation, experimentation, and optimization using various ML algorithms and validation techniques.
• Build and maintain automated pipelines for data processing, model training, and evaluation.
• Monitor model performance, track data drift, and identify production issues.
• Collaborate with data scientists, engineers, and product teams to deliver business-focused ML solutions.

Requirements:

• 1+ years of experience in machine learning or data science projects.
• Strong proficiency in Python with hands-on experience in: NumPy, Pandas, Scikit-learn, Matplotlib / Seaborn
• Experience in data preprocessing, feature engineering, and handling large datasets.
• Good understanding of ML concepts such as model evaluation, cross-validation, overfitting, and feature importance.
• Proficiency in SQL for data extraction and analysis.
• Familiarity with Git and collaborative development workflows.
• Strong analytical and problem-solving skills.
• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or a related field.
• Knowledge of fintech, credit risk, or business analytics domains.
• Basic understanding of MLOps, model deployment, and pipeline automation.
• Passion for continuous learning and exploring emerging technologies in machine learning and AI.

Skills

Python, SQL, data science, machine learning