Quantitative Strategist at MassMutual
Why we need you.
We’re growing, and our clients deserve the best. Our Data Science Development Program spans a maximum of three years. At the advanced level, the program offers opportunity for more independence in project work. Coursework / development component of the program is a combination of programming and computer science and statistics.
Objectives of this role – What success looks like:
- Emphasis is on building self-reliance in the application of skills to real world data science problems.
- Incumbents demonstrate technical competency across a wide range of dimensions.
- Individuals at the advanced level are capable of producing high quality, production-ready deliverables.
Daily and monthly responsibilities – What your days and weeks will include:
- Participating in project setup, discussion of approaches and methods, data strategies, ETL processes, carrying out statistical analysis, programming in R or Python, design and build visualizations, hypothesis generation, data source identification and validation, presenting and explaining output and, gathering business insights.
- Pare generally conducted in a small team environment with a mix of data scientists, product managers, and business owners/subject matter experts.
- Incumbents are expected to fully participate in executive presentations and discussions at the culmination of each of these projects.
- Incumbents are responsible for collaborating across functions and business units and working effectively in small, fast paced team environments.
- Incumbents are expected to contribute to inventory of project work, as with any other team member.
- Incumbents are capable of contributing resources that assist with team development and learning.
Required skills and qualifications – The qualifications that are needed for this role:
- Advanced degree in statistics, applied mathematics, engineering, computer science or related field
- Experience with finance concepts
- 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 or machine learning/deep learning techniques for classification, prediction and optimization
- Experience working in an agile environment
- Excellent written and oral communication
- Ability to seek guidance and learn new skills from peers
- Authorized to work in the US with sponsorship
Preferred qualifications – Additional skills that make you a great fit:
- PhD in a quantitative field
- Ability to navigate complexity and ambiguity and formulate innovative and practical next step
- Entrepreneurial minded and driven self-starter
- Experience with Vertica
- Experience within the financial services industry