Description

You will design and develop analytics models using statistical and machine learning algorithms to solve complex business problems.

Responsibilities

• Design analytics models for forecasting, prediction, segmentation, recommendation, and fraud detection.
• Build end-to-end machine learning solutions and implement them in production environments.
• Prepare and clean raw data using Python frameworks, including imputing missing values and standardizing formats.
• Develop infrastructure to support large-scale data analytics and experimentation.
• Augment internal data with third-party sources to enhance analytics capabilities.

Required Skills

• 5+ years of experience in data analytics.
• 4+ years of continuous experience with Spark, specifically PySpark implementation.
• Strong proficiency in Python and Python-based machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with Pandas, NumPy, and Jupyter Notebooks for data exploration and processing.
• Expertise in core statistical algorithms, including classification and regression analysis.
• Experience using Databricks for large-scale data processing.
• Knowledge of analytics use cases such as language analysis, assortment optimization, dynamic pricing, or labor scheduling.
• Graduate degree in Computer Science, Mathematics, Physics, or a related field.

Preferred Skills

• PhD in a quantitative field.

Key Skills

Education

Graduate degree in Computer Science