Lead Product Business Intelligence Analyst

at  Americor

Americor is seeking a Lead Product Business Intelligence Analyst to join our team. The Lead Business Intelligence Analyst for product will have proven experience driving organizational change with data through product outcomes, standing up new analytical capabilities, championing the use of best practices, and staying current with the latest and greatest in the field of data analytics. This role will partner with internal stakeholders on key success measures and provide insights to drive company improvement. Key deliverables include pairing product thinking with developing diagnostic reporting, completing analysis, aiding in the design and measuring of experiments, and creating accurate predictive models. This role will have a significant impact in shaping a customer-focused and data-driven culture through product-focused deliverables.
Compensation: $100,000-$130,000, depending on experience.
Work Location: Irvine, CA.

ABOUT US:

Americor is a leading provider of debt relief solutions for people of all backgrounds. We offer a variety of services to help our clients achieve financial freedom, including debt consolidation loans, debt settlement, and credit repair. Our dedication to others sets us apart – not only as a company but as a community of employees who support each other’s personal and professional growth. Recognized as a ‘Top Place to Work’ and ‘Best Company’ for our outstanding service and commitment to excellence.

REQUIREMENTS:

• Bachelor’s degree in a quantitative field with 4+ years experience or 7+ years equivalent experience.
• Advanced proficiency with SQL (DML, DDL, query optimization).
• Intermediate proficiency with a statistical language; Python preferred.
• Intermediate proficiency with a data visualization tool; Tableau preferred.
• Proven ability to position oneself to advise and teach across a data organization.
• Strong background in product analytics.
• 3+ years experience in product analytics, including experimental design, measurement, reporting, causal inference, and tracking of key objectives.

• Initiate and own new and sustainable analytical capabilities for product data strategy.
• Partner with product managers and engineers to ensure data is properly tagged and captured.
• Initiate and own audits to identify trends and concerns, apply standardized practices, investigate and confirm hypotheses related to product usage, and reinforce best methods for data analytics.
• Stay current with the latest trends and developments in product data analytics; champion internal adoption and change management of the latest practices.
• Answer challenging product questions every day with data and recommendations through reporting, analysis, experimentation, and modeling.
• The reporting created should be diagnostic in design and simple to use.
• Analysis should exhibit concise storytelling with clear insights and actionable recommendations.
• Experimentation should be statistically sound in design and measurement.
• Modeling should accurately predict or score using an appropriate approach and confidence.