Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.
Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 350,000 neighborhoods across 11 countries.
Meet your Future Neighbors
As an Analytics Engineer 4 with Nextdoor, Inc. (San Francisco, CA) (May telecommute from any U.S. location) you’ll:
Apply mathematical or statistical theory and methods to design, create, and select the appropriate samples of data that will allow the data science team to conduct probabilistic experiments and statistical analyses
Design software systems and processes to gather data in the most efficient way and determine key data points needed in order to interpret experiment results and ensure results are properly tracked
Interpret data and report conclusions drawn from their analyses
Work with cross-functional teams, including product, design, engineering, marketing, operations, and sales, to determine which data analyses will lead to the most actionable insights
Build data pipelines to create and transform data for analysis of different product features
Clean and summarize data to make it accessible for reporting and for data science
Combine data from multiple sources to make and distribute client reports in order to see how particular ad products are performing
Analyze expected vs actual delivery of ad products in order to find and improve gaps in our delivery pipeline
What You’ll Bring to The House
Master’s degree or foreign equivalent in Mathematics, Statistics, Business Analytics, or closely related quantitative field.
Three (3) years of years of experience in the role or in a related position.
Full term of experience must include the following: Utilizing Data Analysis tools, such as Databricks or Snowflake, to support and improve business; Utilizing Python and Structured Query Language (SQL) programming languages to conduct large scale data analyses; Utilizing data processing languages, including, Airflow or Alteryx, to build big data pipelines to extract and transform data; Utilizing Tableau or Looker to generate reports and build dashboards and analyze data and create data insights; Utilizing advanced MS Excel Functions, including VBA coding, Pivot Tables, and Power Point, to present project reports and recommendations to leadership teams; and Utilizing data analysis skills to collect large data sets to uncover and visualize hidden insights in core data.