Company Description:
As a leading global investment management firm, AB fosters diverse perspectives and embraces innovation to help our clients navigate the uncertainty of capital markets. Through high-quality research and diversified investment services, we serve institutions, individuals and private wealth clients in major markets worldwide. Our ambition is simple: to be our clients’ most valued asset-management partner.
With over 4,400 employees across 51 locations in 25 countries, our people are our advantage. We foster a culture of intellectual curiosity and collaboration to create an environment where everyone can thrive and do their best work. Whether you're producing thought-provoking research, identifying compelling investment opportunities, infusing new technologies into our business or providing thoughtful advice to clients, we’re looking for unique voices to help lead us forward. If you’re ready to challenge your limits and build your future, join us.
Describe the role:
Day to day responsibilities will include:
- Manage a team of 6-8 investment data analysts responsible for daily data oversight workflows, data incident resolution, and data platform quality improvement projects.
- Relentlessly improve the data quality rules engine by developing smarter exception detection logic using a combination of supplemental/corroborative data and cross-checking statistical/structured and non-structured data analysis (including artificial intelligence/machine learning) algorithms.
- Play a lead role in the onboarding of new datasets by determining the data quality control requirements, and the feasibility of additional oversight workflows that avoid generating exception “noise”.
- Mentor team members during data quality test brainstorming sessions and SQL/Python code reviews.
- Provide periodic team performance reports which measure productivity by the number of test results reviewed, new tests developed, and the number of false versus true positive versus true versus false negatives detected (noise versus signal).
- Undertake bespoke requests for data analysis.
- Assist the data engineering team in the testing of new data feeds / pipelines, ensuring job controls include data timeliness and completeness checks.
- Handle data collation, cleansing and analysis (SQL, Python).
Preferred Skill Sets:
- 6+ years of experience of investment data analysis and/or data management operations
- 4+ years small to medium size team management / leadership
- 2+ years of SQL / Python scripting experience to support data analysis.–
- Broad understanding of key investment data domains: market data, fundamental and macroeconomic data, positions and transactions, risk and investment performance analytics
- Excellent project management / organization skills: ability to manage competing task priorities based on business impact -
- High level of attention to detail and accuracy, relentless focus on improving team productivity
- Working experience on building quantitative models; experience with factor research, portfolio construction, systematic models -
- Academic qualification in Mathematics/Physics/Statistics/Econometrics/Engineering or related field
- Understanding of company financial statements, accounting and risk analysis would be an added advantage
- Strong (English) communication skills with proven ability to interact with global clients
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