ML & Data Science Engineer

Primary Responsibilities: • Design machine learning systems to automate predictive models. • Develop ML algorithms to analyze historical data to make predictions. • Run tests, performing statistical analysis, and interpreting test results. • Develop and support data pipelines to extract, transform and load data into Google Data Center data warehouse. • Demonstrate ability and willingness to learn quickly and complete large volumes of work with high quality. • Demonstrate outstanding collaboration, interpersonal communication and written skills with the ability to work in a team environment.

Minimum qualifications: • Bachelor's degree in a quantitative discipline (e.g., Statistics, Computer Science, Math, Physics, Engineering), or equivalent practical experience. • 3+ years of experience in analytics or similar fields. • Experience with scripting languages (e.g. Python, Perl, etc.). • Experience manipulating data sets in SQL and using statistical software (e.g., R, SAS, MATLAB, Numpy/Pandas). • Experience in software engineering, including gathering data for analysis, performing data filtering and preparation, and running tests at scale.

Preferred qualifications: • Master's degree in a quantitative discipline. • Experience in machine learning (e.g., supervised learning, clustering). • Experience designing data models or table schema. • Experience writing and maintaining extract, transform, and load scripts which operate on a variety of structured and unstructured sources. • Knowledge of statistics (e.g., probability theory, hypothesis testing, regressions), and experimentation theory