Senior Business Analyst

Hammerjack Pty Ltd; Taguig; Hybrid; PHP 1,000,000 - 1,500,000; Full time

Job summary

Hammerjack Pty Ltd is seeking a Senior Business Analyst to bridge treasury/finance operations with AI-driven data science. The role emphasizes understanding liquidity, FX, and instrument flows while interfacing with data scientists.

The ideal candidate will map data, identify relevant business variables, and translate complex financial concepts into actionable insights for executives in a hybrid work setup.

Qualifications

• Deep domain knowledge in treasury, corporate finance and liquidity management.
• Ability to map data, understand data lineage and data quality.
• Comfort with data visualization to present AI insights to executives.

Skills

Treasury & Corporate Finance

Data literacy

SQL proficiency

Agile/Scrum

Education

Bachelor's degree in Finance/Accounting/Business

Tools

Power BI

Tableau

Job description

Senior Business Analyst

Business Analyst (BA) for a Treasury or Finance AI project, you need a hybrid professional who bridges the gap between complex financial operations and data science. A standard IT BA will struggle with the financial nuances, while a pure financial analyst will struggle with machine learning workflows.

Required Skills:

1. Domain Expertise (Treasury & Corporate Finance)

The BA must deeply understand what they are trying to automate or predict. Look for strong knowledge in:

• Cash Flow Forecasting: Understanding liquidity management, working capital cycles, and variance analysis.
• Risk Management: Knowledge of foreign exchange (FX) hedging, interest rate risk, and counterparty risk.
• Financial Instruments: Familiarity with money market funds, commercial paper, bonds, and derivatives.Treasury Systems: Experience working with Treasury Management Systems (TMS) (like SAP Treasury, Kyriba, or Quantum) and ERP systems (Oracle, SAP).

2. AI & Data Literacy (The AI Bridge)

They do not need to code algorithms, but they must speak the language of Data Scientists.

• Data Mapping & Lineage: Ability to identify where financial data lives, its format, and how clean it is. (AI projects fail without clean data).
• Feature Engineering Input: The capacity to tell data scientists which business variables matter (e.g., Quarter-end seasonality affects this cash flow line item).
• Understanding Model Limitations: A foundational grasp of how Machine Learning (ML) works, including concepts like training data, over-fitting, and confidence scores.
• Explainable AI (XAI): The ability to help translate a black-box AI prediction into a rationale that a Chief Financial Officer (CFO) or Treasurer will trust.

3. Core Business Analysis & Agile Delivery

• Requirement Gathering for Unpredictable Outputs: Unlike traditional software, AI outputs are probabilistic (predictions), not deterministic (fixed rules). The BA must be skilled at defining acceptance criteria for probabilistic data.
• SQL Proficiency: Must-have ability to query databases independently to validate data assumptions before handing them to the development team.
• Data Visualization: Experience using tools like Power BI or Tableau to mock up how the AI insights will be delivered to executives.
• Agile/Scrum Framework: Experience working in iterative sprints, managing product backlogs, and writing user stories.