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Department Profile Bloomberg's Index and ESG Research team supports the Index business in the development of custom indices as well as ESG product development. The role reports to the head of the Index and ESG Research team within the broader Portfolio Risk and Index Quant Research group.
Job Summary We are seeking an applied scientist to join an active research team focused on index design among various asset classes and investing strategies. The successful candidate will be responsible for developing a research platform that enables exploration of new ideas and improving research productivity. It is expected they will also collaborate and advise on multiple research initiatives. A successful candidate will be also be passionate about our area of domain expertise - the opportunity to offer data-driven approaches to investment and portfolio construction.
Develop an integrated research platform for identifying investment signals, constructing portfolios and quantifying portfolio characteristics.
Participate in index and ESG research projects
Collaborate with a diverse group of researchers and with data, product and engineering teams to encourage development and broad re-use of common tools.
Communicate clearly through face-to-face meetings, presentations and written publications
Deliver complex projects with multiple stakeholders
Perform literature reviews and keep apprised of trends in data science and quantitative investment strategies
The candidate should have expertise in the theory and implementation of quantitative analysis techniques, including knowledge and experience with a range of data sources and statistical analysis. -The candidate must also have experience in implementing data and analytics platforms in Python. -Additionally, the candidate should have either the knowledge or ability to learn techniques related to portfolio construction and sustainable finance analysis.
Key qualifications include:
Master's or PhD degree in Computer Science, Engineering, Mathematics, Statistics, or a similarly quantitative field
Expertise with data models, data structures and algorithms
Ability to design for efficient, scalable computation
Experience with statistical models that apply cross-sectional and time-series econometrics, dimensionality reduction, and optimization techniques
Fluency with Python, GitHub and the software development lifecycle.
Proficiency with Unix shell environments.
3+ years of experience working on a team dealing with data-intensive modeling
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.