Founded in 1999 and based in San Mateo, California, SurveyMonkey is the world’s leading platform for turning people’s voices and opinions into actionable data — People Powered Data. Whether it’s with customers, employees, or a target market, SurveyMonkey helps curious individuals and companies — including 99% of the Fortune 500 — have conversations at scale with the people who matter most. It’s People Powered Data that allows them to understand not only “what” is happening, but “why.” SurveyMonkey’s 700+ employees throughout North America, Europe, and Asia Pacific are dedicated to powering the curious.
The Data and Analytics team at SurveyMonkey is looking for a Director of Data Science to lead and develop a team of data scientists who implement tools and technologies to help our customers and internal constituents achieve extraordinary value. We are looking for someone to join our team to lead groundbreaking R&D projects, to leverage massive structured, unstructured, transactional and real-time data sets from a variety of sources, analyze financial and customer usage patterns and make actionable recommendations using machine learning, data mining, business understanding and common sense.
If you are a statistics and machine learning whiz (a.k.a. data scientist) who is equally at home discussing a project with business owners, researchers or developers, thrives on accelerating business growth, is willing to roll his/her sleeves up and do the hard work, can build, grow and motivate a team, has developed code that is used in production, has lead a team before, and is extremely creative, collaborative, innovative – yet disciplined, methodical and down to earth – we want to hear from you. Especially if you can parse this paragraph.
Work with us as we develop and apply state-of-the-art big-data techniques in our cloud infrastructure, where your work will directly impact the success of our customers and SurveyMonkey.
In detail you will:
- Build, grow, motivate and mentor a team of data scientists
- Implement a solid development, evaluation, deployment and refinement methodology for data science projects
- Interact with internal clients and product managers to understand their requirements for predictive analytics applications
- Help develop and test predictive algorithms to be implemented as part of internal tools and customer facing applications
- Understand business goals and initiatives, and combine business modeling skills with outstanding data analysis
- Cooperate with the Data Engineering team to design and execute replicable data acquisition and utilization processes
- Cooperate with the Personalization Engineering team to integrate models into production code
- Cooperate with BI teams to deliver forward looking insights into our business
In order to solve these challenges, you should be able to leverage off-the-shelf or open-source technologies as well as in-house engineering, and feel comfortable with big data solutions, applications and infrastructure:
- Advanced degree (M.Sc., Ph.D. preferred) in statistics, math, CS or another relevant field.
- 5+ years of industrial data-mining / analytics experience including applied techniques in data mining, machine learning, NLP or graph mining
- 3+ years of experience leading a data science team
- Extensive development experience in Python (incl. Pandas, Numpy, Scipy)
- Experience with SQL (Hadoop and Spark experience is a plus)
- Experience turning ideas into actionable designs and delivering solutions to end users. Able to persuade stakeholders and champion effective techniques
- Comfort working in a dynamic, research-oriented group with several ongoing concurrent projects
- Strong verbal and written communication skills as well as excellent presentation skills
- Publications at relevant scientific conferences and journals is a plus
At SurveyMonkey, we offer competitive salaries, medical/dental benefits, PTO, 401k, paid holidays, and equity compensation.
SurveyMonkey is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.