Key job responsibilities include, but are not limited to:

• Conducting asset allocation, portfolio construction and manager selection research, utilizing the team’s existing processes and infrastructure as well as new data and techniques;
• Undertaking bespoke research, data analysis and portfolio optimization projects for external and internal clients;
• Working closely with AB investors on a range of investment-related problems relating to Strategic Asset Allocation, portfolio construction and portfolio management;
• Presenting research findings and SAA and other recommendations to internal investors
• Assisting with and supporting the managing of portfolios run by the team;
• Assisting in producing thought-leadership research publications (from short blogs to white papers)
• Engaging and communicating with clients on bespoke projects and participating in client presentations;
• Collaborating with sales and Business Development colleagues on identifying commercial opportunities and creating and pitching new and existing investment solutions to clients;

Examples of more technical/analytical aspects of the job include but are not limited to:

• Building dashboards for data visualization (Python Dash)
• Handling data collation, cleansing and analysis (SQL, Python)
• Creating new databases using data from different sources, and setting up infrastructure for their maintenance;
• Cleaning and manipulating data, building models and producing automated reports using Python;
• Using statistical modelling and Machine Learning to address quantitative problems and conduct research (Python)

Job Qualifications

• 3-5 years total work experience, including 3+ years experience in a quantitative research role relating to capital markets. strategic asset allocation and/or portfolio analysis/risk/portfolio optimization. Preferred background in addition to buy-side multi-asset quantitative research may include:investment banking, management consulting, sell-side research
• Experience of RDBMS database design, preferably on MS SQL Server
• Advanced skills with programming using any of Python libraries (pandas, numpy, statsmodels, dash, pypfopt, cvxpy, keras, scikit-learn)  
• Ability to manipulate large quantities of data
• High level of attention to detail and accuracy
• 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) oral and written communication skills with proven ability to interact with global clients
• Intellectually inquisitive and motivated to achieve, with a record of outstanding academic and professional success
• Have an analytical personality that is attracted to problem solving
• Be equally comfortable working in a team environment and independently