Staff Finance BI Analyst: COGS & Analytics Lead

DIVERGENT; Los Angeles (CA); Hybrid; USD 163,000 - 225,000; Full time

Benefits offered by this job

Equity plan

Discretionary incentive bonus

Health insurance

Paid time off

Job summary

Divergent is seeking a Staff Business Intelligence Analyst (Finance) to drive analytics that measure financial metrics and optimize cost data across the manufacturing, planning, and production domains at our Los Angeles base. You will build end-to-end finance analytics, including COGS, cost structures, and data pipelines, partnering with teams across software, ERP, and operations.

The role emphasizes hands-on development in Python and SQL, with focus on robust data architecture, governance, and

Qualifications

• Bachelor’s degree in a related field such as Finance, Accounting, Data Science, or Economics.
• Demonstrated application development experience using Python and SQL.
• Experience with ERP systems (Oracle Fusion, SAP) and cost data analytics.

Responsibilities

• Scope, deliver, and maintain analyses to enhance reporting on financial metrics, owning end-to-end development and adoption.
• Collaborate cross-functionally to deliver scalable solution architecture.
• Review business processes and recommend changes for robust data collection and analytics.
• Participate in regular cross-functional reviews to ensure milestones and schedules are understood.

Skills

Python

SQL

Data analysis

Cost accounting

Interpersonal skills

Education

Bachelor’s degree in Finance/Accounting/Data Science/Economics

Tools

Oracle Fusion

SAP

Job description

Divergent is seeking a Staff Business Intelligence Analyst (Finance) to drive analytics that measure financial metrics and optimize cost data across the manufacturing, planning, and production domains at our Los Angeles base. You will build end-to-end finance analytics, including COGS, cost structures, and data pipelines, partnering with teams across software, ERP, and operations.

The role emphasizes hands-on development in Python and SQL, with focus on robust data architecture, governance, and