Quantitative Strategist
We are building a modern finance organization, where quantitative methods are employed to generate actionable financial insights. We seek an experienced Quantitative Strategist to join our team. As a strategist, you will be working alongside interdisciplinary teams, including certified public accountants, actuaries, product managers, business analysts, portfolio managers, and leaders throughout the organization, to identify and test hypotheses to improve the financial performance of MassMutual. Our team is intellectually curious. You will apply business logic and modern statistical methods, including machine learning and deep learning, to build predictive models. With these tools, Quantitative Strategists will analyze existing models and identify potential improvements, create tools to automate research, and improve visualization of complex data sets. You’ll join a team of innovative, collaborative, and resourceful people who think differently, think big, and persevere through all challenges.
Key role responsibilities
- Partner with Corporate Finance and business unit functions to solve critical business problems using advanced analytics, artificial intelligence, including machine learning, in domains such as:
- Capital optimization
- Investment performance
- Forecasting of sales and asset and liability stocks
- Expense and resource optimization
- Identify high value use cases and pragmatic approaches to generate financial insights
- Assess solution options and algorithms to support analysis
- Rapidly prototype and develop analytical models to identify insights and deliver predictions
- Identify integration needed to operationalize insights into reporting or other planning/forecasting processes and tools
- Work with data engineering and digital reporting teams to automate analysis, integrate and scale model
Required Qualifications
- Masters Degree in statistics, applied mathematics, engineering, computer science or related field
- Experience with finance concepts and sales, expenses, and income
- Experience applying advanced analytical techniques to time series data
- Experience with data analysis using R or Python (numpy, spark mllib, scipy, matplotlib, scikit-learn, pandas, etc.) programming languages
- Extensive experience with using SQL to query and prepare data
- Experience with common statistical, optimization, machine learning/deep learning techniques for classification, prediction and optimization
- Experience working in an agile environment
- Authorized to work in the US with sponsorship
Preferred Qualifications
- PhD in a Quantitative Field of Study
- Ability to navigate complexity and ambiguity and formulate innovative and practical next step
- Ability to seek guidance and learn new skills from peers
- Excellent written and oral communication
- Entrepreneurial minded and driven self-starter
- Experience with Vertica
- Experience within the financial services industry