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, FactSet, 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 BlackRock Aladdin, FactSet, 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, FactSet, 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
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