About Team Go
We use technology to inspire and empower humanity, and to enrich real-life relationships with friends, family, and community because we believe in a world where social technology unites us and makes us happier. We started on this mission by putting together a team of people to fix social isolation and bring people together to do things they love.
By looking at how people make plans with one another, we built the Go app around peoples’existing behaviors, like sharing plans with our friends, inviting friends to collaborate, finding time to hang out--and making it all happen in real time, in real life.
We also want the local businesses in your community to be part of the conversation, which supercharges the Go app and helps you find what you love to do and do it with the people you already know.
The Role
This is a high precision position. A successful Senior Data Scientist, specializing in measurements and visualization, is a person who loves exact science. Since this position is equal parts statistics, data management, and data visualization, there are many touchpoints to manage at all times.
The Senior Measurements and Visualization Data Scientist at Go will have a deep understanding of requirements gathering, stakeholder management, project oversight, and technical implementation. This position requires a rare combination of management and build capability. As a result of being an early hire in the Measurements unit, the successful applicant will have a heavy contributory hand in both the tools selected and protocols in place as the unit is fully staffed.
This job will not be easy- we are looking for a candidate who likes to solve hard problems and build out their own team.
The right candidate will have the right combination of inventiveness, managerial skills, and technical know-how.
Responsibilities
- Build, refine, and scale internal product oversight tools
- Build, refine, and scale dynamic, client-facing B2B-centric dashboards
- Visualizations lead - all internal and external dashboard-related data cleaning, analysis, visualization, and interpretation
- Measurements lead - Conduct initial and ongoing assessment of necessary internal and client-facing analytics requirements
- Oversight - gather and maintain systemic knowledge of all pertinent data at all stages of the data lifecycle- from capture to storage to analysis.
- With the help of the data security referent, ensure all data in transit and at rest is compliant with protocol.
- Manage end-user and business serial cross-sectional surveys. Ensure data captured is valid and field teams receive ongoing quality assessments.
- Research, create, and deploy new end-user and business surveys as needed (new markets or research question evolution)
- Automate survey data cleaning, storage, and descriptive analytics.
- Create and maintain survey data dynamic analytics dashboard, which allows for, at minimum, variable cross tabulation.
- Perform additional predictive analyses of survey data at regular intervals and as needed by leadership.
- Present relevant findings from all sources to senior staff in a format that is relevant, actionable, and replicable.
Important Skills
- Knowledge of product performance analytics.
- Strong understanding of advanced statistics, including but not limited to causal inference, principles of regression (linear, logistic, et al), model fitting, power calculations, sampling methodology for heterogenous populations, hierarchical modeling, longitudinal modeling, multi-population comparative analyses, time series analyses
- Strong data visual representation knowledge
- Dashboard creation
- Univariate, bivariate, and multivariate visualization best practices
- Data Visualization software packages, including but not limited to C3, D3, Victory Labs, or equivalent JS custom dynamic dashboarding library
- HTML, CSS
- Hierarchical and longitudinal analysis using STATA
- Hierarchical and longitudinal analysis using R
- Predictive Analysis - Linear regression
- Predictive Analysis - Logistic regression
- Predictive Analysis - non-logit regression (Poisson, Probit, etc.)
- Causal Inference assessment using directed acyclic graphs
- Decision tree creation and interpretation
- SQL database management, including advanced query scripts
- Rest API management (MongoDB- Javascript)
- Scripted data cleaning and de-duplication
- Python and Javascript knowledge a plus
- Familiarity with internal, product-focused analytics tools, such as StatHat, Google Analytics, Status Cake, Apollo GraphQL Studio, and AWS CloudWatch
Qualifications
- Advanced degree (Masters or PhD) in any of the following:
- Statistics
- Economics
- Computer Science
NOTE: Advanced degrees with quantitative-heavy focus to be assessed for relevance.
- 2-3 years of experience in a senior capacity
- At least 3 years experience as a working statistician, data scientist, or quantitative analyst.
- Samples of their work:
- At least 3 data analyses
- At least 3 data visualization examples
- At least 1 publication
- Previous experience as a data scientist in a senior role with analogous tasks and competency requirements.
- Previous project management / project oversight experience a plus.