Primary Responsibilities:

Design machine learning systems to automate predictive models.

Develop Client 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:

Masters 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.