Foursquare is the leading independent location technology company, powered by our deep understanding of how people move throughout the world. Our solutions help businesses make smarter decisions, developers create more engaging experiences, and brands build more effective marketing strategies.
Foursquare’s platform includes Attribution, Audience, Proximity, Places, Pilgrim SDK and Visits. As the industry’s first and only accredited company for location data from the Media Rating Council (MRC), this foundation powers all our solutions — those that exist today and those we have yet to build. Over 14 billion consumer-verified place visit confirmations help us keep our map and models fresh and up-to-date, building a phone’s-eye-view of the world with 105 million unique places of interest worldwide.
About the role:
As a member of Foursquare’s data science team, you’ll be responsible for supporting statistical inference, big data analytics, and supervised/unsupervised model building. The methodologies we employ are varied which creates a rich environment for the application of data science technology. This is not just a machine learning job. We look for data scientists who are excited by the challenge of solving problems using a wide array of modeling and quantitative techniques. This can involve product feature prototyping, new metric development, and exploratory data analysis. Data scientists at Foursquare are also highly collaborative, working largely with Product and Engineering stakeholders to deploy machine learning models and analytics processes at scale in production.
Responsibilities of the role
- Build supervised/unsupervised machine learning models and support feature engineering
- Build statistical inference and big data analytics
- Create prototype code and documentation for model implementations
- Work with software engineers to implement and deploy machine learning models and data analytics into production
- Conduct ad-hoc data investigation and data-driven approaches for insights extraction
- Work with product team and core clients to scope requirements and communicate project status
- Proactively Identify and implement product and process changes to make the platform more efficient and accurate
- Strong problem solving and data-driven decision making skills
- Advanced degree (MS, Ph.D) in quantitative field of study (computer science, applied mathematics, statistics, etc.)
- Four years work experience in quantitative roles
- Proficiency in prominent programming languages used for data science and analytics (Python or R, as well as SQL)
- Proven problem solver, with a track record of successfully uncovering data insights that lead to positive business impact
- Proven track record of delivering on products and/or practical research endeavors
- Experience with Hadoop, Spark, Databricks, AWS EMR, or similar frameworks
- Experience with data visualization tooling (Tableau, AWS QuickSight, Grafana)
- Comfort with Unix/Linux and the command line
- Experience with geospatial data
- Industry experience in advertising technology
Perks and benefits:
- Learning and development programs from ICs to managers
- Individual, professional coaching for all full-time employees
- Flexible time off - rest and recharge when you need it!
- Comprehensive and competitive health, vision, dental, life insurance
- 401(k) with company match
- Home office setup: you get all necessary hardware and internet reimbursement
- Family planning programs via Carrot and Maven
- Employee Resource Groups to help you stay connected
Foursquare is proud to foster an inclusive environment that is free from discrimination. We strongly believe in order to build the best products, we need a diversity of perspectives and backgrounds. This leads to a more delightful experience for our users and team members. We value listening to every voice and we encourage everyone to come be a part of building a company and products we love.
Foursquare is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law.