At a Glance
- Tasks: Analyse and validate financial data, producing insightful reports and dashboards.
- Company: Join a leading investment management firm focused on data excellence.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous improvement and innovation.
- Why this job: Make an impact in finance by enhancing data quality and driving insights.
- Qualifications: 2-6 years in data analysis with strong SQL and Python skills.
The predicted salary is between 82440 - 100760 $ per year.
Key Responsibilities
- Perform day‑to‑day data analysis and validation activities across the client’s data ecosystem.
- Analyse, reconcile, and validate investment and operational data to identify trends, anomalies, and data quality issues.
- Track, investigate, and resolve data exceptions, escalating issues where required.
- Support ongoing data feeds and integrations across platforms such as Aladdin, Fact Set, custodians, and internal reporting tools.
- Produce recurring and ad‑hoc reports, dashboards, and analytical outputs for internal teams and client stakeholders.
- Support change initiatives by validating data impacts and assisting with user testing and post‑implementation checks.
- Collaborate with vendors and internal teams to improve data quality, timeliness, and consistency.
- Candidate Profile
The successful candidate will have
2 - 6 years of experience in data analysis, reporting, or data operations, ideally within investment management, financial services, or consulting environments.
- Strong experience working with structured datasets, including performance, reference data, benchmarks, and portfolio/account data.
- Hands‑on experience with analytical tools such as
SQL, Python, Excel , and BI platforms (e. g. Power BI, Tableau).
- Exposure to investment management systems such as
Black Rock Aladdin, Fact Set, Axioma, or similar platforms .
- Demonstrated ability to perform data reconciliation, exception analysis, and root‑cause investigation.
- Strong attention to detail and a commitment to data accuracy and quality.
- Ability to communicate analytical findings clearly to non‑technical stakeholders.
- Experience working in multi‑stakeholder environments with internal teams, vendors, and clients.
- Main Tasks
- Analyse and reconcile data across upstream and downstream systems, identifying discrepancies and trends.
- Support data mastering activities, including security reference data, benchmarks, FX rates, and portfolio structures.
- Assist with performance and attribution data validation and reporting.
- Investigate data exceptions and contribute to root‑cause analysis and remediation documentation.
- Build and maintain dashboards, reports, and automated analytical outputs using SQL, Python, and BI tools.
- Support continuous improvement initiatives, including process optimisation and automation of manual data tasks.
- Contribute to documentation, SOPs, and data quality metrics reporting.
- Data Analysis
- extracting, transforming, and analysing data to produce insights.
- Data Quality & Reconciliation
- validating completeness, accuracy, and consistency of data.
- Reporting & Visualisation
- building dashboards and reports for operational and management use.
- Investment Data Knowledge
- understanding securities, portfolios, benchmarks, and performance data.
- Process Improvement
- identifying inefficiencies and supporting automation initiatives.
- Stakeholder Communication
- explaining analytical outcomes clearly and concisely.
- Collaboration
- working effectively across technology, operations, and client teams.
- Technical Skills
- SQL (advanced querying and data validation)
- Python (data analysis, automation, scripting)
- Excel (advanced formulas, pivots, data modelling)
- BI tools (Power BI, Tableau, or similar)
- Exposure to investment management platforms (e. g. Aladdin, Fact Set, Axioma)
- Professional Skills
- Strong analytical and problem‑solving capability
- High attention to detail
- Clear written and verbal communication
- Ability to manage multiple priorities and deadlines
- Continuous learning mindset, particularly around data tools and investment systems
- #J-18808-Ljbffr
Financial Data Analyst in Melbourne employer: Invartis Consulting
As a Functional Project Manager at our company, you will thrive in a dynamic work environment that values collaboration and innovation. We offer competitive benefits, a supportive culture that encourages professional growth, and the opportunity to lead impactful projects within the Enterprise Data Management framework. Located in a vibrant region, our team is dedicated to fostering a workplace where your contributions are recognised and rewarded, making it an excellent choice for those seeking meaningful employment.
We think you need these skills to ace Financial Data Analyst in Melbourne
Data Analysis
Data Validation
SQL
Python
Excel
BI Tools
Investment Management Systems
