Minimum qualifications:

　　6 years of industry experience, with 4 years of experience in machine learning or software engineering.

　　Experience with machine learning frameworks such as TensorFlow, Scikit-Learn, design, implementation and delivery of scalable build/test/release agile software development cycle.

　　Experience with data processing and management with both Relational Database Management Systems (RDBMS) and with programming in one of the general programming languages (e.g., Python, Java, Scala, C++).

　　Preferred qualifications:

　　Experience with cloud platforms such as GCP.

　　Experience in full-stack development for machine learning solutions.

　　Knowledge of front-end development.

　　Excellent written and verbal communication skills to translate technical solutions and methodologies to senior leadership.

　　As a Quantitative Analyst, you will be responsible for analyzing large data sets and building expert systems that improve our understanding of the Web and improve the performance of our products. This effort includes performing complex statistical analysis on non-routine problems and working with engineers to embed models into production systems. You will manage fast changing business priorities and interface with product managers and engineers.

　　As a Business Data Scientist in Machine Learning Engineering, you will work on solving technical challenges across multiple business areas through the lens of business generation. You will collaborate with data scientists, analysts, and product managers to accelerate the creation of data solutions to enable finance partners to make informed decisions, manage risks, and opportunities.

　　Work cross-functionally with data scientists, data engineers, and program managers to understand, implement, and deploy machine learning pipelines.

　　Improve machine learning scalability, usability, and performance.

　　Explore technologies and apply them to deliver business benefits.

　　Provide support for processes, standards, and engineering practices.

　　Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCPEEOPost.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.