Finance Data Analyst

Key Responsibilities

• Data Collection and Analysis: Collect, analyse, and interpret data from various sources and complex transactions to identify trends, and insights that inform data solutioning processes
• Data Quality Assurance: Assist in data validation efforts to ensure datasets meet end users’ requirements to deliver high quality product releases, and continuous support in monitoring data quality and resolving data discrepancies
• Collaboration: Work closely with cross-functional teams, including data engineers, business analysts and stakeholders, to gather data requirements and ensure data integrity
• Enhancements: Identify opportunities for process improvement and operational efficiency
• Research and Learning: Deeply understand client’s relevant business activities, commercial interests and related processes, and continuously expand your knowledge and skills in data analytics techniques and tools

Skills & Qualifications

• BS/MBA in Finance, Accounting, Economics, Business Analytics or BS/MS in STEM or quantitative field (CS, Applied Statistics, Operations Research)
• 2-4 years of financial/business/data analyst experience
• Knowledge of accounting principles, financial statements, and financial modelling
• Understanding of Data Design Pattern differences between transactional ERP systems (SAP) and analytical data warehouses (BigQuery, Snowflake)
• Knowledge of SQL and working with large datasets
• Experience with data analytics tools and languages (R, Python…)
• Experience building interactive data visualizations, strong storytelling skills (Tableau, Streamlit, Shiny…)

Secondary Skills:

• Experience building/applying statistical and/or machine learning solutions to solve business problems
• Ability to self-start and self-direct work in an unstructured environment, comfortable dealing with ambiguity
• Excellent problem-framing, problem solving and project management skills, with the ability to change direction quickly
• Strong verbal and written communication skills with ability to articulate results of analysis in business terms
• Confirmed ability to conduct complex, data driven analysis
• Ability to work independently and collaboratively in a fast-paced environment
• Eagerness to learn and adapt to new tools, techniques, and technologies in the field of data analysis