Data Scientist

Zocdoc•New York, NY

6d•$165,000 - $175,000

About The Position

Zocdoc is hiring a Data Scientist to analyze data and answer product and business questions. The role includes working with large datasets, identifying business problems that can be addressed through analysis, designing and interpreting experiments and causal analyses, investigating changes in metrics, and communicating findings and recommendations to stakeholders. The Data Scientist partners with Product, Engineering, and Data Engineering to validate metric definitions, experiment setup, and measurement readiness, and documents analytical methods and conclusions so the work can be understood and reused. The position is based at the job site in New York, NY, with remote work permitted on occasion within a commutable distance from the worksite. It is a 40-hour-per-week role. The posting lists an annual salary of $165,000–$175,000 for the role and also provides an NYC base salary range of $130,000–$170,000 USD.

Requirements

Bachelor’s degree or foreign equivalent in Business Analytics, Engineering (any), Math, or a related field.
Two years of experience in the job offered or a related quantitative occupation.
Two years of experience reviewing business intelligence, dashboarding, reporting, and data analytics using Tableau, Looker, BigQuery, and AWS (S3) to monitor key metrics, analyze trends, and deliver insights supporting process execution, financial analysis, and product development.
Two years of experience analyzing statistical modeling, causal analytics, and experimental design using R (including R Shiny) and SQL to produce actionable insights for product strategy, financial outcomes, and business decisions.
Two years of experience manipulating large datasets using Python and Snowflake for data extraction, cleaning, transformation, and workflow automation for reporting and analysis.
Two years of experience using Tableau, Looker, and visualization tools including Figma, FigJam, and Miro to translate analyses into dashboards, reports, and visual insights and communicate recommendations to product, finance, and business stakeholders.

Responsibilities

Analyze, manipulate, or process large datasets using statistical software.
Clean and manipulate raw data using statistical software.
Identify business problems or management objectives that can be addressed through data analysis.
Recommend data-driven solutions to key stakeholders.
Create graphs, charts, and other visualizations to convey results of data analysis.
Execute end-to-end analyses to answer product and business questions.
Use SQL and analytical programming tools to extract, transform, and analyze data accurately and reproducibly.
Design and analyze experiments using valid frameworks, interpret results, and surface limitations, assumptions, and uncertainty.
Investigate metric changes and evaluate plausible drivers.
Partner with Product, Engineering, and Data Engineering to validate metric definitions, experiment setup, and measurement readiness.
Document analytical context, methodology, assumptions, and conclusions so work can be understood and reused.
Communicate findings clearly and concisely, focusing on how results answer the underlying business question.
Identify potential data quality or measurement issues and escalate them appropriately.
Design methodologically sound causal analyses for complex initiatives and interpret results appropriately.