Description

You will bridge the gap between data engineering and statistical analysis to drive business growth and revenue.

Responsibilities

• Design and execute experiments, including A/B testing and hypothesis development, to generate actionable business recommendations.
• Build and manage databases, data warehouses, and dashboards to visualize key metrics and inform decision-making.
• Perform customer segmentation, user profiling, and churn analysis using large, unstructured datasets.
• Implement predictive analytics and statistical modeling techniques such as GLM, multiple regression, and logistic regression.
• Mine and collect data from diverse on-premises and cloud-based systems.

Required Skills

• 5+ years of experience monitoring, managing, and manipulating data to derive insights.
• Proficiency in Python, R, and SQL, including complex querying with multiple tables and subqueries.
• Experience with big data tools including BigQuery, PubSub, and MapReduce.
• Strong background in statistical modeling, variable selection, and data mining.
• Hands-on experience with data visualization tools such as Tableau, DataStudio, d3.js, or ggplot.
• Ability to work with massive, unstructured datasets and perform effective statistical interpretation.
• Bachelor's degree in Computer Science.

Preferred Skills

• Experience with Google technologies including Protocol Buffers, Bigtable, Spanner, and Bazel.
• Knowledge of machine learning algorithms and algorithmic thinking.

Key Skills

Education

Bachelor's degree in Computer Science