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 London, UK