This role will have oversight of the alpha research environment within the equity and high income divisions and will be directly supporting activities ranging from quantitative research to alternative/unstructured data analytics. The director will manage a team of Quantitative Specialists responsible for monitoring all calculation/reporting production cycles, fielding requests for custom analyses, and participating in development efforts to expand research capabilities. The incumbent will serve as a subject area leader on all aspects of alpha research and the broader data environment, while leading complex multi-team projects of varying size from both a project management and technical implementation perspective.
Assume leadership of all alpha research responsibilities involving Investment Research Services, including management of the vision and roadmap relating to project planning, ownership of meeting schedules and agendas, coordination of resources to maximize productivity, and development of the partnerships with the research and technology departments.
Serve as a mentor and subject matter expert for junior team members to ensure they are pursuing optimal approaches across all aspects of their workload from a technical and content standpoint, while also keeping them engaged, motivated and operating at their full potential.
Develop deep understanding across all aspects of alpha research including model construction, factor definitions, factor calculations, and translating output statistics into meaningful information used within the portfolio management function.
Consult with internal and external business partners as part of the expansion and maintenance of the investment research data environment.
Perform business/systems/data analysis, detailed process design, and thorough acceptance/quality testing across projects that require new content, perform complex analytic calculations, and produce additional reporting capabilities used by 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 Research Analysts in addition to frequent high priority inquiries from other senior investment professionals.
Education and Experience
8-10 years of experience in an investment data analytics capacity, preferably with people management responsibilities.
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.
Investment industry experience, preferably in investment research or a portfolio analytics function of an investment management company.
A Bachelor’s degree in finance, math, accounting, engineering, or computer science. Master’s Degree and/or CFA Charter are strongly desired.
Skills and Knowledge
Advanced level SQL and ability to traverse large database schemas across diverse content sets.
Experience with Python, R, and/or VBA.
Experience with stock selection models and machine learning/AI techniques are a plus.
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.
Familiarity with quantitative analytics, including fund and index performance measurement, predictive risk modeling, alpha research, and performance attribution.
Strong hands-on project leadership skills with the drive to complete complex projects as a part of small teams within an extremely fast paced environment.
Capability to liaise with investment professionals to gather requirements and manage deliverables of technical development teams.
Knowledge of securities, corporate actions, financial statement analysis, street estimates, pricing and performance data.
Highly proactive and self-motivated with the ability to meet objectives under minimal supervision.
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