Data Scientist (Masters)

The efficacy of AI models is directly proportional to the quality and relevance of their training data. As a Data Scientist (Masters), you will play a crucial role in shaping AI's understanding of complex data patterns, feature engineering, and robust model evaluation, driving the development of more intelligent and reliable AI systems.

Key Responsibilities

• Design and curate intermediate-level datasets for AI training, focusing on machine learning algorithms and statistical modeling.
• Evaluate AI-generated feature engineering strategies for relevance, dimensionality reduction, and predictive power.
• Assess AI's performance in model evaluation metrics (e.g., precision, recall, F1-score, AUC) and cross-validation techniques.
• Provide expert feedback on AI-proposed solutions for data preprocessing, outlier detection, and imputation methods.
• Formulate and validate complex data science problems for AI to solve, spanning classification, regression, and clustering tasks.
• Identify and correct logical inconsistencies in AI's interpretation of statistical inference and hypothesis testing.

Ideal Qualifications

• Master's degree in Data Science, Computer Science, Statistics, or a related quantitative field.
• 2 years of practical experience in data analysis, machine learning, or predictive modeling.
• Proficiency in Python (scikit-learn, pandas, numpy) and/or R.
• Solid understanding of supervised and unsupervised learning algorithms.
• Experience with SQL and data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Ability to explain complex data science concepts clearly and concisely.