Posted 2 days ago
Data Operations#
AI Summary
Maintains and quality-checks client, pricing, valuation and portfolio datasets across platforms, tracking data exceptions to resolution within SLA and supporting ad hoc data extractions for investment stakeholders.
About this role
Maintain dataset across multiple platforms (ex: new clients, pricing, valuations and portfolio details) based on procedures and protocols.
Perform data quality control checks, liaising with Subject Matter Experts (SMEs) as required
Carry out exception reporting and resolution tracking. Ensuring aged and critical exceptions are resolved within the agreed SLA.
Develop competence with internal systems and processes
Support ad hoc data extractions requests from internal stakeholders
Develop and maintain robust processes to ensure data is accurate and meets business needs
Have the opportunity to take ownership of projects and processes.
Assist with the documentation of processes
Develop technical expertise and collaboration within the team and across the Investments business
The successful candidate will be expected to work within the existing risk management and audit framework of the team and business, which includes checklists and review processes, branded ‘Professional Excellence’. All team members are encouraged to contribute ideas for process improvements.
Throughout you will benefit from the business’s focus on training and development, including soft-skills, investment knowledge and data expertise.
Qualifications
- Bachelor’s degree completed or currently in the final semester in Finance, Business Administration, Actuarial Science, Data Science, or a related quantitative or business field.
- Academic, internship or early-career exposure to data management, finance, investments or other data-intensive environments.
- Understanding of Data Management principles on areas of sourcing, cleansing, transformation, validation, etc. will be advantageous.
- Proficiency in English, both in written and verbal communications.
- Proficiency in Microsoft Office.
- Strong attention to detail, with the ability to identify inconsistencies, missing information and potential data-quality issues.
Strong organizational and analytical skills, with the ability to follow established processes and manage recurring data-related activities accurately.
Nice to Have:
- knowledge of R or Python coding (is a plus).
- Advanced knowledge or certification in automation tools (Power Automate) is desirable but not mandatory.
- Familiarity with Power Automate or other automation tools, desirable but not mandatory.
Equal Opportunity Employment
Skills
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