Description

You will develop and deploy predictive models using Python and R, performing statistical analysis and implementing machine learning algorithms to structure and visualize data.

Responsibilities

• Develop and deploy predictive models using Python and R.
• Perform statistical analysis, including hypothesis testing and missing data analysis.
• Implement machine learning algorithms such as ensemble methods and clustering.
• Generate high-quality data visualizations to communicate findings.
• Apply dimensional modeling techniques to structure data.

Required Skills

• 4+ years of experience in model development and deployment.
• Proficiency in Python, R, and SQL.
• Hands-on experience with Pandas and Scikit-learn.
• Strong understanding of statistics and machine learning fundamentals.
• Experience with GLM methods and outlier detection.
• Practical knowledge of ensemble methods including Random Forests, XGBoost, and AdaBoost.
• Experience with clustering algorithms like K-Means, K-Medoids, and DBSCAN.
• Ability to create visualizations using Matplotlib and Seaborn.
• Familiarity with dimensional modeling, including facts, dimensions, and surrogate keys.

Preferred Skills

• Experience with PowerBI or Tableau.
• Knowledge of time series forecasting methods.
• Actuarial background or experience.

Key Skills

Education

Any Graduate