Data Scientist (geospatial)

We are seeking a mid-level data scientist to join WeWork’s data science team and improve our ability to make data-informed geospatial decisions, such as where to locate our WeWork co-working and WeLive co-living spaces.

WeWork is expanding rapidly. We already have more than a hundred WeWork coworking locations in a dozen countries on four continents. And, we have plans for many more. But where? Which cities? Where in the city? What predicts a good location? Do we add another location to an existing city or should we branch out into a new metro? What’s the appropriate mix of office sizes and facilities for a city or building?

We want to hire a data scientist to form a matrixed team with market analysts, developers, and other domain experts to build predictive models and tools to help the business make data-driven geospatial decisions.

This person will be part of a larger data science team embedded within the centralized data team. The central data team’s job is to support analysts and decision makers across the organization, and to support you. We want you to focus on making awesome, impactful predictive models.

 Why this role is important

In this role, you will get to influence key strategic decisions such as site selection. These will have a profound effect on the business, shape our product offering, possibly for decades.

While WeWork is very data-driven, there is an ever-expanding need to use data science to continually improve decision-making. You have the chance to showcase what data science can achieve, increase broad buy in and enthusiasm, and change the culture. There is a general thirst to use data in more creative and powerful ways and you can help showcase what can be achieved.

 What you will learn

There is a lot of potential to learn new skills in this role. You are going to learn how to work with the business, how to determine the best problems to tackle, and how to tackle them with ML. Of course, you get the chance to beef up your data science chops. You will have the independence and responsibility to own these projects, choose the right models, and see them through to completion. You are going to learn interesting new data sources, develop new approaches, and possibly new visualizations. If you’ve not worked with data from a global organization, in multiple languages, you’ll certainly learn that too.

 Responsibilities

  • Collaborate with stakeholders and rest of team to help identify, scope, and prioritize appropriate problems to tackle.
  • Hypothesize and explore potential correlates, predictors, and causal factors.
  • Identify potentially useful new data sources.
  • Prototype and explore potential computational and machine learning approaches.
  • Build, and ultimately productionize, predictive models for a variety of geospatial problems.
  • Work with team to deliver analyses and results in the best way to impact decisions.

 Requirements

  • 4+ years practical experience in industry as a data scientist or similar quantitative role.
  • Very strong experience in the geospatial domain and tools. You can write code to Google Maps API in your sleep. You’ve an opinion about map projections and the best hexagonal tiling library. You could explain Haversine distances right now.
  • You’ve a sound understanding of GIS principles and tools. Ideally, you’ve previously used ArcInfo, ESRI, GRASS, PostGIS and the like.
  • You love hacking on geodata. You’ve got a portfolio of interesting spatial projects, demos, and other work you are dying to share.
  • Track record of prototyping, developing, and deploying statistical and ML models.
  • Strong SQL skills. Experience with production transactional and data warehouse databases. (We primarily use AWS Redshift.)
  • Strong technical skills, especially in Python (numpy, scikit-learn, pandas etc), R, and *nix command line.
  • Deep knowledge of machine learning and data mining.
  • Superior communication and data visualization skills. You can tell a compelling story with data.
  • Experience working in an Agile environment

 Nice to have

  • Full stack experience, someone who could prototype a data product, soup to nuts.
  • A Master’s or Ph.D. in quantitative relevant subject (such as science, computer science, statistics, or machine learning) is preferred but far more important is your proven, industry track record.

 Critical Competencies for Success

  • You do what you love!
  • You are infinitely curious.
  • You are a collaborative doer who can work independently to get things done.
  • You love to learn. Love to mentor and teach others, even better.
  • You thrive in a dynamic startup environment. You live KISS and embody agile.
  • You keep up-to-date with latest developments in the field

About WeWork

WeWork is the community of creators. We provide the space, community and services for over tens of thousands of members to do what they love and create their life's work. WeWork’s mission is to build a world where people work to make a life, not just a living. Our own team members are central to this mission.

The WeWork team is a group of entrepreneurial, grateful individuals who deeply believe in what we are creating and in the power of “we”. We challenge convention and achieve amazing things through dedication and collaboration.

WeWork transforms buildings into beautiful, collaborative work spaces and provides infrastructure, services, events and technology so our members can focus on doing what they love. Our team members value the WeWork concept and there is a contagious energy in our offices as we work towards accomplishing our goals.

Our hunger for building great spaces, empowering small businesses and connecting interesting people hasn't yet begun to be satisfied. We are just getting started, and our journey gets increasingly more exciting as team members join our mission!

Our values guide who we are and everything that we do.

Inspired

We do what we love and are connected to something greater than ourselves.

Entrepreneurial

We are creators, leaders and self-starters.  We try new things; we challenge convention; and we’re not afraid to fail.

Authentic

We are genuine to our brand, mission and values.  We’re not perfect and we don’t pretend to be.  We are, though, always honest and as transparent as we can be.

Tenacious

We never settle.  We get sh*t done and we get it done well.  Be persistent and knock down walls – literally if you have to.  You have our permission.

Grateful

We are grateful for each other, our members, and to be part of this movement.  We don’t take success for granted.  We’re happy to be alive.

Together

We are in this together.  This is a team effort.  We always look out for one another. We value empathy; we know we’re all human, and know we can’t do any of this alone.


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