Business Analyst II

Aston Carter•Los Angeles, CA

3d•$35 - $38•Onsite

About The Position

The Business Analyst II leads the onboarding of key forecasting models including promo sign-ups, subscription churn, and total customers into a financial forecasting platform built on TM1 and related planning tools. This role serves as the primary bridge between Finance stakeholders and TM1 engineering, translating finance reporting requirements and model logic into clear technical specifications, coordinating implementation, and owning user acceptance testing. The Business Analyst II also produces thorough documentation for each model build and enhancement, and establishes a repeatable framework for onboarding new models into the forecasting platform.

Requirements

4 to 6 years of experience as a Business Analyst or Systems Analyst working with finance systems or enterprise planning tools.
Proven experience translating business requirements into detailed technical specifications for engineering teams.
Demonstrated ability to assess existing business processes and design improved workflows, including creating wireframes and UI/UX proposals.
Advanced Excel skills, including complex formulas, pivot tables, data modeling, and scenario analysis.
Working knowledge of SQL, with the ability to query relational databases to validate data and trace data lineage.
Experience with planning, executing, and documenting user acceptance testing (UAT).
Strong written and verbal communication skills, with the ability to articulate complex concepts to both technical and non-technical stakeholders.
Solid understanding of financial reporting and forecasting concepts, with the ability to support accurate and reliable financial outputs.

Nice To Haves

Experience with TM1, Planning Analytics, or similar enterprise planning and forecasting tools.
Familiarity with ETL pipelines and data warehouse concepts, including platforms such as Redshift, Andes, or comparable technologies.
Knowledge of FP&A concepts, including forecasting, actuals versus plan variance analysis, and dimensional modeling.
Experience working within media, streaming, or subscription-based business models.
Ability to collaborate effectively with Data Science, Data Engineering, and Finance stakeholders in a cross-functional environment.

Responsibilities

Gather and document detailed finance reporting requirements from Finance stakeholders and translate them into precise technical specifications for TM1 and associated planning tool implementations.
Define data requirements and source-data contracts for each forecasting model, identifying gaps between existing Finance Excel models and current system capabilities, and proposing solutions within TM1 and planning tool constraints.
Design and wireframe user interfaces and user experiences for forecast adjustments to ensure that users can easily access only the adjustments they need to make, with complete reporting visibility after updates.
Partner closely with TM1 engineering teams to design, build, test, and deploy updates to Finance models within the TM1 and planning analytics environment.
Develop and execute comprehensive user acceptance testing (UAT) plans, validating that cube changes and model updates produce accurate and financially correct outputs before release to production.
Document business rules, calculation logic, and data lineage for all onboarded forecasting dimensions to ensure transparency, consistency, and maintainability.
Identify gaps in platform validation checks and collaborate with TM1 and planning tool teams, Data Science, and Data Engineering to strengthen validation and data quality controls.
Trace metric discrepancies across multiple reporting surfaces back to pipeline-level or cube-level root causes, and work with relevant teams to resolve issues.
Own the TM1 engineering ticket queue end to end, including intake, tracking, and closure of tickets, while prioritizing strategic work and new issues based on business impact in partnership with the Finance team.
Maintain clear, structured documentation and communication around model changes, data requirements, and workflow improvements to support ongoing platform evolution.