Team Go · Nov 19th 2020
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.
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.
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.
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
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
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
Scripted data cleaning and de-duplication
Familiarity with internal, product-focused analytics tools, such as StatHat, Google Analytics, Status Cake, Apollo GraphQL Studio, and AWS CloudWatch
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.