Financial Data Analyst
2 weeks ago
What we are looking for (Banking Sector Client):
- DA Adoption: Candidate to possess knowledge of how data analytics can be deployed the financial strategy (Treasury) space. & to demonstrate the ability to find creative solutions and improvise effectively in dynamic environments
- Although preferred, previous experience in Treasury/FTP/Bank's Balance Sheeting Reporting is not essential. But has to possess strong interest in bank's business with an inquisitive/investigative nature to pick up on banking sensibility/financial reporting concepts.
- Data Quality/Data Validation/Manual Data Checks
- To support strategic initiatives in covering Group balance sheet / funds transfer pricing reporting & review.
- To support buildup of, and "data mine" finance related data for Group reporting.
- To support buildup of Group balance sheet / funds transfer pricing modelling tool.
- To support Business-as-usual Fund Transfer Pricing processes and reporting
- Any ad hoc assignment in relation to balance sheet, liquidity and returns review.
- To perform ad hoc assignment in relation to business finance role for Central Treasury Unit (CTU) which includes monthly/quarterly T&I reporting, management adjustments.
- Assist in any other duties as assigned.
- Assist the team in any ad hoc admin work and projects as assigned.
- Job rotation may be required as and when advised.
Functional Skill Set:
- Min 3 years experience in data analytics/data science, preferably in the banking/financial services sector. Experience in data analytics, SQL, Python programming.
- Basic understanding (is preferred): Bank's Treasury, Fund Trunsfer Pricing, Bank's Balance Sheet/Profit & Loss Statemements, Financial Product Control, Liquidity, Basel.
- Proficient in MS Excel, able to use pivot tables and VLOOKUP effectively.
- Experience in data analytics, SQL, Python programming preferred.
- Possess good analytical skills and problem-solving skills.
Technical Skill Set:
- Mandatory to have: SQL Query, Python (Matplotlib, Pandas, NumPy, Scikit-learn, Seaborn, SciPy, TensorFlow, Plotly, Keras), VBA Macros/Advanced Excel
- Good to have: Power BI/Tableau, Hadoop and Discovery tools (eg Qliksense, HUE), Metadata tools (eg Informatica Metadata Manager)
Bonus Points For:
- Experience in gathering and documentation of functional business requirements.
- Knowledge of architecting and modeling in Systems Integration, Data Warehousing, BI tools, Big Data platforms, and experienced in the use of analytical query and visualization tools. Must be able to query and understand database solutions.
- Experience designing, developing, and documenting data-driven solutions – including capturing architectures, metadata systems, data dictionaries, databases, and application
QlikSense
TensorFlow
Pandas
Data Analysis
Data Mine
ETL
VBA
Data Quality
SQL Query
Data Mining
Management Accounting
Balance Sheet
Banking
Data Science
Consolidated Financial Statements
Vlookup
Python Programming
Data Analytics
Treasury Management Systems
Matplotlib
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