Manulife Investment Management - Quantitative Development Analyst

paid / Boston, Toronto / Full-time


Proficiency in writing code in R or Python.
Designing interactive web applications using R Shiny or Python Dash
Databases (PostgreSQL, MS SQL Server, Hadoop/Spark, Redis)
Cloud infrastructure (Linux and Docker on Azure/AWS)
Data visualization (R Shiny, Power BI, Tableau, Plotly/Dash)
Other investment data/tools (FactSet, Bloomberg, S&P Capital IQ, Morningstar, vendor APIs, etc.)

Manulife Investment Management’s Quantitative Development team is a small group with a broad mandate to design and implement investment analysis at scale—from the firm-wide to the security-level—for $500B+ in investments across the global Wealth and Asset Management segment.

The team’s goal is to help the firm deliver more alpha, more efficiently. We do this by:

· Partnering with equity, fixed income, and multi-asset investment groups to enhance existing investment process

· Developing scalable solutions to complex problems in areas such as:

-- macroeconomic forecasting
-- portfolio construction and optimization
-- alpha signals
-- security valuation
-- trade allocation
-- investment screens
-- ESG integration

· Providing quantitative analysis on strategies to global Chief Investment Officers and investment teams

· Applying scalable frameworks on large data sets and effectively communicating research, process, and output to non-technical audiences

Essential Responsibilities:

Due to the wide variety of projects, your work will often require a hybrid mix of skills -- not only in investment management, but also in analytics, technology, data, innovation, project management, and visualization. You will help us build new processes while also helping us maintain, adapt, and enhance existing ones.

We are heavy users of technology to get things done at scale – due to the large number of strategies, asset classes, desks, teams, portfolios, sectors, securities, and data sources to cover. As such, though experience with programming and databases is not initially required, gaining proficiency in R and SQL will be expected. We will provide extensive training as needed.

Ability to scale our analytical capabilities is a valued skill, distinct from the analysis itself. Senior team members are expected to do both, so you will be expected to progressively enhance your depth and breadth of skills.

Job Requirements:

SKILLS/CHARACTERISTICS: Must have strong desire and ability to learn new things, have an entrepreneurial mindset (you will be building lots of things entirely from scratch!), and have an interest in financial markets.

Must be comfortable with a consistent focus on creativity and innovation, as the group is structured by design to tackle only complex challenges—often things never done before inside the firm—and to scale team capacity through automation. (We strive to never do the same thing twice.)

Must demonstrate a strategic orientation, for example:

-- Developing generalized, scalable solutions to problems and/or applying systems-level thinking to avoid fragile, one-time solutions where possible
-- Thinking beyond the immediate ask (i.e., to what is someone really asking for), understanding the client’s deeper needs, and building strong relationships

EDUCATION/EXPERIENCE:

-- Preferred: 5-10 years relevant work experience within the financial industry (e.g., portfolio management, quantitative analysis, investment data science, etc.)
-- 2-10 years of programming experience (R or Python preferred). Experience with R Shiny or Python Dash is a big plus
-- Progress towards CFA or advanced degree a plus
-- Salary commensurate with experience.

TECHNOLOGY/DATA:

Experience with some of these a plus, but extensive training will be provided as needed:

-- Proficiency in writing code in R or Python.
-- Designing interactive web applications using R Shiny or Python Dash
-- Databases (PostgreSQL, MS SQL Server, Hadoop/Spark, Redis)
-- Cloud infrastructure (Linux and Docker on Azure/AWS)
-- Data visualization (R Shiny, Power BI, Tableau, Plotly/Dash)
-- Other investment data/tools (FactSet, Bloomberg, S&P Capital IQ, Morningstar, vendor APIs, etc.)


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