Description

Build and maintain machine learning and statistical models through the entire development lifecycle.

Responsibilities

• Develop ML and statistical models from data acquisition and feature engineering through production and monitoring.
• Apply scientific methods to practical problems using exploratory data analysis, hypothesis testing, and data visualization.
• Manipulate, integrate, and process large datasets to ensure data quality and accessibility.
• Communicate complex technical topics to both technical and non-technical audiences.
• Solve ambiguous, undefined problems with minimal oversight.

Required Skills

• 5+ years of experience in data science or a related field.
• Proficiency in Python and SQL.
• Experience with big data technologies including Hive, Hadoop, and Spark.
• Hands-on experience with machine learning algorithms such as SVM, KNN, logistic regression, random forest, XGBoost, and Neural Networks.
• Strong understanding of statistical probability distributions, bias, error, power, and sampling methods.
• Experience using GitHub and participating in CI/CD processes.
• Ability to perform deep data interrogation and large-scale dataset processing.
• Degree in any graduate field.

Key Skills

Education

Any Graduate