Quantitative Analyst
The Advice Engines Quantitative Analysts are highly visible representatives of our Advice Engines Product Team. The Quantitative Analysts analyze large data sets and condense complex information into concise, relevant, and easy to communicate results. They assist in the implementation and maintenance of statistical software applications, research databases, and other data products. In addition, they are responsible for creating original investment research that empower investor success.
Responsibility:
• Integrate proprietary research and asset allocation concepts into a global set of advice engines by working closely with Morningstar research, product managers, and developers to bring intellectual property and new methodology to market
• Familiarity with Numerical optimization techniques and Monte Carlo approaches to asset allocation analysis
• Present results to audiences with varied technical backgrounds: other team members, sales organization members, and advisors
• Contribute unique ideas, insights, expertise and experience to other research projects through formal and informal collaboration
• Faithfully present the work of the Quantitative Research team to internal stakeholders and external clients
• Generate original investment research with the goal of improving outcomes for our clients
• Assist in the development of production applications that incorporate numerical techniques such as linear algebra, machine learning, statistics, and optimization
• Become a subject-matter expert in multiple investment vehicles such as equities, fixed income instruments, mutual funds, exchange-traded funds, etc., as well as Morningstar’s proprietary methodology and data points
Requirements:
• A bachelor’s degree in science, engineering, finance, or math is required. A bachelor’s degree in math/statistics is preferred
• Strong attention to detail, excellent verbal, written, and analytical skills
• Ability to multi-task and manage several projects at any given time
• Ability to collaborate, act as a team player, communicate across various layers of the organization, and work in cross-functional distributed teams
• Proficiency in statistical modeling language (R or Python) as well as SQL
• Expertise in Morningstar's mutual fund, fixed income, and equity databases
• Expert level proficiency in Microsoft Excel (including use of macros and VBA programming)
• Expertise and in statistical methods and modelling
• Preferably >3 years’ experience in multi-asset research and portfolio management in investment industry
• Good experience of software engineering and writing scalable, performance efficient codes using Python, MATLAB, R.
• Familiarity with portfolio construction, asset allocation, Capital Market Assumptions, factor modelling, risk and return attribution, asset return forecasting, portfolio optimization, Monte Carlo simulation.
• Working knowledge of the how advisors/wealth managers provide advice and solve common investor problems: accumulation, retirement income.
• Strong command of foundations of applied and theoretical statistics, linear algebra and vector manipulation, and machine learning techniques
• Understanding of the nuances and pitfalls of common models and modeling approaches, such as analyzing time-series based data vs. other types
• Proficiency in statistical modeling language (R or Python) as well as SQL
• Expertise in Morningstar's mutual fund, fixed income, and equity databases
• Expert level proficiency in Microsoft Excel (including use of macros and VBA programming)
• Expertise and in statistical methods and modelling