Job Description

Quantitative Research Services is a part of the Fidelity Asset Management Quant Research & Investments (QRI) organization and provides analytic solutions and data management services to quantitative researchers, portfolio managers and senior leadership roles across Asset Management.  This specialized team leads development efforts to expand and enhance the technical infrastructure and reporting capabilities associated with multi-factor model risk forecasting, quantitative alpha research, big data analytics, and performance attribution.  Together with their partners in the technology and research divisions, members of this organization work as an integral part of small project teams to deliver innovative data visualization and analytic tools capable of illustrating current and time series investment themes, portfolio exposures, and factors driving fund performance. 

The successful candidate will explore and model non-traditional datasets to be incorporated into and enhance the investment process.  You will analyze and transform a wide range of structured and unstructured big data to accelerate the evaluation and adoption of new capabilities into quantitative research and investment products.  As part of this process, you will deliver production-grade data curation and analysis methods and techniques.

The Expertise You Have:

A Bachelor’s degree in computer science, finance, math, or engineering. Master’s Degree and/or CFA Charter are strongly desired.
5-10 years of software engineering experience in a modern quantitative language.
Demonstrated history as a top performer working in a data analysis role where technical skills were required. 
Successfully led medium to large sized projects in a fast-paced environment.

The Value You Deliver: 

Leverage your technical skills to rapidly explore and prototype new content and methods to help evaluate their value through proofs-of-concepts.
Develop deep understanding of existing data models and quantitative research processes to seamlessly extend our data platform.
Perform business, systems, and data analysis, process design, and acceptance testing across projects that require new research content, investment analytics, and/or produce additional reporting capabilities for investment professionals. 
Oversee daily/weekly/monthly production reporting cycles across the analytic environments.  Ensure all required input data is available, processes run successfully, statistical output is accurate, and reports are generated properly. 
Respond to ad-hoc data analysis requests in support of projects performed by quantitative researchers in addition to frequent high priority inquiries from other senior investment professionals.
Contribute to the continued development and incorporation of non-traditional and/or unstructured data as well as data science applications to enhance the research and investment process.

The Skills You Bring:

Strong programming in Python (NumPy, Pandas, Scikit-Learn) with the ability to develop customized quantitative tools.
Experience with SQL and ability to traverse a wide array of database schemas across diverse content sets. 
Highly analytical with the ability to quickly comprehend large data sets in order to develop new processes, perform calculations, identify anomalies, and/or produce new reporting capabilities.
Experience in Big Data, NLP, and text search technologies such as Elasticsearch and Solr.
Experience with object-oriented languages and user interface programming skills (Java, C++, Angular, C#/.Net).
Lead the implementation of a research project through the entire software development lifecycle utilizing a full-stack implementation.
Highly proactive and self-motivated with the ability to meet objectives under minimal supervision.
Experience with Cloud-based platforms preferred (AWS, Snowflake, etc.)
Financial knowledge and experience analyzing and applying AI/ML techniques to time-series market and economic data