Senior Quant Research Analyst: Asset Allocation & Portfolio

AllianceBernstein; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

AllianceBernstein in London is seeking a quantitative researcher to advance asset allocation and portfolio optimization work. You will conduct research, build models and dashboards, and collaborate with investors on strategic questions.

You will analyze large data sets with Python, SQL, and ML techniques, producing insights for internal clients and external discussions. Strong math background and communication skills are essential.

Qualifications

• 3-5 years total work experience with 3+ years in quantitative research related to capital markets.
• Experience with RDBMS design and MS SQL Server preferred.
• Advanced Python skills with libraries (pandas, numpy, statsmodels, dash, scikit-learn).
• Ability to manipulate large data sets and build quantitative models.

Responsibilities

• Conduct asset allocation, portfolio construction and manager research using established processes and new data techniques.
• Undertake bespoke research and data analysis for external and internal clients.
• Collaborate with AB investors on strategic asset allocation and portfolio management questions.
• Present findings and recommendations to internal investors.
• Support portfolio management activities and client communications.
• Create and contribute to thought leadership publications.
• Engage with clients on bespoke projects and support sales opportunities.

Skills

Python

SQL

R

Pandas

Numpy

Dash

Machine Learning

Data Visualization

Portfolio optimization

Education

Mathematics/Statistics/Econometrics degree

Tools

MS SQL Server

Python libraries

Job description

AllianceBernstein in London is seeking a quantitative researcher to advance asset allocation and portfolio optimization work. You will conduct research, build models and dashboards, and collaborate with investors on strategic questions.

You will analyze large data sets with Python, SQL, and ML techniques, producing insights for internal clients and external discussions. Strong math background and communication skills are essential.