Data Scientist 4

Overview

Responsible for extracting insights from high-volume, high-dimensional data to solve complex business problems using data preparation, modeling, analysis, and/or visualization.

What you'll do

• Build machine learning pipelines for creation, testing, deployment, monitoring, and maintenance.
• Consolidate and analyze unstructured big data sources to generate actionable insights.
• Apply data manipulation and ML workflows for EDA, feature extraction, modeling, and hyperparameter tuning.
• Conduct correlation analysis, classification/clustering, anomaly detection, and time series forecasting.
• Integrate insights with client services and product enhancement.
• Develop clean, modular, maintainable Python code using best practices.
• Support and mentor junior to mid-level data scientists and ML engineers.

What you'll need

• 5+ years of commercial experience in machine learning pipeline lifecycle activities.
• Fluency with data manipulation and ML frameworks for EDA, feature extraction, development, modeling, and experiment tracking.
• Expertise in correlation analysis, classification/clustering, anomaly detection, and time series forecasting.
• Strong Python background with ability to write clean, modular, maintainable code.
• Experience with SQL for data exploration, feature extraction, and integration into analytical workflows.
• Familiarity with cloud platforms such as Google VertexAI, BigQuery, CloudSQL, Compute Engine, or similar solutions.

Nice to have

• PhD in a relevant field.
• Networking/telecommunications knowledge.
• Experience with data visualization tools/frameworks like Dash, Streamlit, and Superset.

Details

• Employment experience range stated: 7–10 years.