Data Scientist - Funnel Optimization - SF - Change.org - San Francisco, CA

Change.org is the world’s largest empowerment platform, used by more than 95 million people around the world to win incredible and inspiring victories on the issues they care about.

We’re an innovative business – a certified “B Corp” combining the structure of a business with a powerful sense of mission that drives our work (more about B Corps: www.bcorporation.net). Over 25 million users have signed winning petitions, including strengthening hate crimes legislation in South Africa; fighting corruption in Indonesia, Italy, and Brazil; ending the ban on gay Boy Scouts in the United States, and big wins for women’s rights in India. And we’re just getting started. Here’s a small snapshot of what was changed last year: www.change.org/2014

We love serving our incredible users, and we love our staff too. We show it with very competitive salaries, five weeks of vacation, robust maternity and parental leave, an amazing culture, free language training (if you want it), and a high impact, low-ego team that can’t wait to learn from you and teach you what they know.

We’re seeking a Data Scientist, focused on funnel optimization, who will own the vision and execution of projects from start to finish.

The ideal candidate is super passionate and very motivated to have an enormous impact on a company that is quite literally helping to change the world. This individual will be flexible and interested in learning new skills, tools, and technologies as necessary. Given our small team size and the scope of our global mission, we must select the right tools as necessary. At any given point in time, you may find team members working with one or more of the following: Redshift, Cassandra, AWS (Elastic MapReduce, SimpleWorkflow, EC2, etc), Spark, Redis, and Dropwizard, driven by Ruby, Python, Java, Go, and Javascript.

We encourage our team members to go to and talk at conferences, our team spoke at Strata, AWS re: Invent and DataWeek.

Depending upon your skills and experience, and what you bring to the table overall, we are also open to considering a Senior Data Scientist role.

Here’s what you’ll do as part of our team:
You will get in early and help set technical/product direction on a Data Science team for a company with millions of users and big ambitions.

Use machine learning techniques to further a social justice mission.

Take the lead on data science research projects and pursue them through production.

Follow the data science methodology and best practices

Own the architecture, delivery, and evolution of interrelated big data systems.

Code, write, and converse daily.

Contribute to back-end distributed systems engineering in implementation/integration/monitoring/maintaining our applied data science/machine learning/etc infrastructure

And here are the skills & experience we hope you have:
Masters in Computer Science, Applied Math, Physics, Statistics or a quantitative field with a strong background in matrix manipulation

4+ years of industry experience in the data science arena and dealing with large volume and variety of datasets

3+ years of professional experience with modeling and analysis, statistics, machine learning, and/or large-scale data mining. Has deep experience in the data science methodology from exploratory data analysis, feature engineering, model selection, deployment of the model at scale and model evaluation by using AB testing in production

Experience with multiple supervised and unsupervised machine learning techniques, such as logistic regression, naïve bayes, decision trees, k-means clustering, and principal component analysis

Broad and deep pattern matching for what matters and what to do about it based on your experience solving real problems at scale in big data and data science.

Led and completed multiple projects using some of: Machine Learning techniques, Python, data visualization.

Specific experience in solving machine learning problems that have very sparse data

Convert research papers covering sparse optimization techniques into practical engineering solutions in production.

Work with other data and engineering professionals—as well as lay stakeholders—to respond to business problems with practical solutions.

Choose the most effective technologies and approaches for a variety of big data and data science challenges, and own application thereof.

Mentor talented and less experienced colleagues.

Communicate clearly and effectively with team members of a variety of backgrounds, skill sets, and roles within the business.