Senior Data Analyst, Platform Science

• 5+ years of experience as a Data Analyst
• 3+ years of experience with reporting and visualization tools such as Looker, Tableau, Domo, etc
• Advanced SQL skills including multiple-table joins, unions, sub-queries, CTE, aggregations, temporary tables, and analytical functions
• Technical expertise regarding all things data, including: mining, modeling, transforming, cleansing, and validating
• Ability to take vague requests and transform them into concise deliverables
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Excellent communication skills, both verbal and written
• BS in Mathematics, Economics, Computer Science, Information Management, Statistics or equivalent experience

Desirable

• The Senior Data Analyst is responsible for processing large amounts of raw information into strategic insights for consumption by our Product, Engineering, and Leadership teams
• The Senior Data Analyst is the face of the Data Team to other parts of the company. This role is highly analytical, utilizes strong SQL skills, and is proficient at creating and presenting visualizations
• This role is a company wide advocate and resource for data informed decision making. They help to mentor and grow the data team both in terms of technical skills and process improvements
• Leverage our modern data stack (dbt, Snowflake, Looker) in order to identify, analyze, and interpret trends or patterns in complex data sets to enable business-critical decisions
• Work closely with our product and engineering teams to define, build, and analyze meaningful KPIs for our applications and systems
• Apply your expertise in quantitative analysis, data visualization and data-mining to create data alerts and derive actionable insights
• Filter, clean, and transform data from a variety of sources in order to enable analysis
• Work with management to prioritize business and information needs
• Locate and define new process improvement opportunities within the data team