Descripción del puesto:
As a Machine Learning Engineer Intern at (COMPANY NAME) working on Capital, you will lead projects that derive value from our unique, rich, and rapidly growing data. Specifically, you will do analysis and build models which will help drive originations and reduce losses for our business loan products.
For this 12-week summer internship in San Francisco, you will:
* Build machine learning models that make critical decisions in an automated manner
* Write production code to deploy machine learning models
* Specific problems you will solve include: How can we detect fraud and avoid making loans to businesses who are unlikely to repay? How should we size loans to balance risk and growth? What, if any, external data should we invest in to improve the performance of our credit models? How do we optimize our marketing? For example, what is the optimal frequency and timing of emails?
* Pursuing an advanced degree (Masters or PhD) in Computer Science, Machine Learning, Statistics, Physical Sciences, Economics, or a related technical field
* Familiarity with Linux/OS X command line, version control software (git), and general software development
* Understanding of machine learning and statistics
* Experience with lending and/or financial data
* Familiarity with Python machine learning libraries (scikit-learn)
* Experience productionizing machine learning models to solve complex business problems
Technologies we use and teach:
* Python (numpy, pandas, sklearn, xgboost, TensorFlow)
* MySQL, Hive
* Google Cloud Platform
At (COMPANY NAME), our purpose is to empower - within and outside of our walls. In order to build the best tools for the businesses and customers we support all over the world, we have to start at home with a workforce as diverse and empowered as our sellers. To this end, we take great care to evaluate all employees and job applicants equally, based on merit, competence, and qualifications. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply and always consider qualified applicants with arrest and conviction records, in accordance with the San Francisco Fair Chance Ordinance.
Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible