Data Analyst

Responsibilities

• Collaborate with Product and Analytics teams to use a combination of exploratory and descriptive analytics to inform product strategy and roadmap, and provide ad-hoc analyses that uncover root cause of recent business trends.
• Understand data infrastructure and coordinate with Data Engineering to deliver data models and structures to meet business demands.
• Assist in the design of relevant data models, including outlining dimensions and measures needed, for answering business questions.
• Establish and implement product data standards and best practices in order to optimize the data collection, fidelity and accuracy. Develop product measurement plans and dashboards to monitor metrics and KPIs.
• Support Sales in deploying and documenting internal dashboards and reporting.
• Ensure optimization and validations initiatives are implemented, tracked and reviewed postproduction.
• Shape, explore and publish data for business analysis or stakeholder initiatives using core Business Intelligence (BI) tools.
• Other duties as assigned.

• 3+ years of experience in using data and analytics to drive business decisions, preferably in a sales or commercial setting.
• Experience with cloud-based data warehouses (e.g., AWS Redshift, Snowflake, Big Query).
• Advanced SQL concepts including joins, CTEs, case statements, stored procedures, data writing, window functions, etc.
• Experience building and maintaining Tableau dashboards and reports for business stakeholders.
• Experience with working with and optimizing data ELT/ETL processes.
• Ability to translate technical data into actionable insights for non-technical stakeholders (e.g., sales rep, managers).
• Experience with creating ad-hoc reports based on business questions and requirements.
• Comfortable working in a fast-paced environment with shifting priorities and quick turnaround requests.

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering, or related field.
• Experience with Sales Force (or other CRM systems) and its data.
• Experience with sales KPIs and reporting metrics (e.g., win/loss rates, conversion %).
• Experience with creating or modifying database tables to support reporting.
• Experience with Python, R, or VBA (e.g., automating report refreshes, data quality checks).
• Experience with scheduling/report automation tools like (e.g., Airflow, Redwood, Tableau Server scheduling).
• Strong Excel skills for quick ad-hoc data analysis, validation, or visualization.