Director, Portfolio Analytics

Fidelity Investments•Boston, MA

1d•$165,000 - $194,000•Onsite

About The Position

Oversees production data management, model integrity, and end-to-end technical support for portfolio management, risk models, and quantitative research platforms, by building quantitative research platforms and tools. Ensures complete data quality coverage, Service Level Agreement (SLA) documentation, and proper team communication. Drives the buildout of new data quality frameworks and tools to streamline teamwork in support of Data Quality (DQ) coverage at scale. Draws on in-depth knowledge of advanced principles, theories, and concepts to create high quality quantitative research solutions for complex projects, applications, and products. Consults with development architects and business on internal service quality control standards, policies, and procedures.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Portfolio Analytics (or closely related occupation) performing multi-asset class analytics in a financial services environment.
Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Portfolio Analytics (or closely related occupation) performing multi-asset class analytics in a financial services environment.
Demonstrated Expertise (“DE”) performing product management and impact analysis on trading and risk analytics in a complex multi-asset class environment (open and closed architecture fund-of-funds structures).
DE debugging differences between economic and accounting views of holdings and assessing their influence on portfolio construction.
DE monitoring and measuring risk for mutual funds.
DE writing specification documents, interpreting business requirements, and creating analytical visualization solutions, using Microsoft Office suite, Visual Basic (VBA), Tableau and Oracle SQL.
DE defining and maintaining operational workflows.
DE creating data quality assurance tools for validating holdings from various vendors (Morningstar, Bloomberg, Index providers and accounting views) and instrument data across multi-asset classes (Equity, Corporate Bonds, Municipal Bonds, Commodities, Derivatives, and Alternative strategies), using Oracle SQL, Snowflake, Python, Microsoft Excel, and Visual Basic (VBA).
DE cleaning, validating, cross-checking, tracking, and documenting changes, anomalies, and inconsistencies in raw data for investment risk analysis.
DE analyzing BarraOne Multi-Asset Class (MAC) risk factor model construction, factor definitions, and calculations.
DE translating equity, fixed income, alternatives risk and stress analytics into meaningful insights used for portfolio maintenance.
DE integrating BarraOne risk models into existing infrastructure, and expanding and enhancing analytic platforms and tools, using Microsoft Excel, Snowflake, Tableau, Oracle SQL, Python, and R.
DE performing investment risk analysis (portfolio performance and risk reporting), using BarraOne Multi-Factor Model (MAC) risk and performance attribution.
DE measuring incremental effects of portfolio construction methodologies.
DE performing fund holdings and returns analysis, using statistical methods and analytical tools – Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA).
DE writing risk model methodologies and specification documents, interpreting business requirements, and creating model performance monitoring reports in Confluence and Microsoft Office Suite.
DE integrating portfolio management workflows into vendor tools (Factset and MSCI BarraOne), using Microsoft Office Suite, Tableau, Oracle SQL, Snowflake, Python, and R.
DE researching and testing methods to improve existing models, using regression techniques, time series analysis, and interest rate models and Monte Carlo simulations.

Responsibilities

Develops new processes, performs calculations, identifies anomalies, and produces new reporting capabilities by analyzing large data sets.
Evaluates the value of new content and methods through proofs-of-concept.
Extends data platforms using existing data models and quantitative research processes.
Translates analytics into model construction, factor definition, and calculation.
Develops and incorporates non-traditional and unstructured data and data science applications to enhance research and investment process.
Performs validations and testing of models to ensure adequacy and reformulate models as necessary.
Presents mathematical modeling and data analysis results to management and other end users.
Formulates and applies mathematical modeling and other optimizing methods to develop and interpret information that assists with decision making.
Collects and analyzes data and develops decision support software, service, or products.
Develops and supplies optimal time, cost, or logistics networks for program evaluation, review, or implementation.
Advises senior management on technical strategy.
Participates in high-level, cross-functional design teams.
Sets vision, goals, and direction of team/organization.
Plans and leads organization-wide initiatives.
Provides leadership, technical supervision, and expertise to multiple teams in broad technical areas on complex organization-wide projects.
Researches and recommends new technologies.
Regularly provides guidance, training, and coaching to other team members for performance and career development.
Identifies and plans for future resource needs.