MassMutual Lead Data Scientist - Actuary/Underwriting in Amherst, Massachusetts
MassMutual’s Advanced Analytics group is seeking an exceptional, highly motivated and self-directed data scientist. In this role, you will perform data-driven research, problem solving, and algorithm development through the systematic application of mathematics, statistics and computer science as well as cutting edge data technologies. Results of this work manifest themselves in a variety of ways, including interactive visualizations, presentations, publications, web applications, predictive algorithms, and APIs.
This is an opportunity to join a small but growing high performing team with diverse backgrounds in applied math, computer science and physics that have been tasked with developing, maintaining and extracting knowledge from a strategic data asset. Our work revolves around studying fundamental and high impact business questions that directly impact the direction of the company and industry at large.
Set strategy and assume a leadership role in actuary and/or underwriting domain
Develop roadmaps for projects and services, data, and technology
Oversee operations of algorithm and system deployments
Partner with executive leadership to ensure alignment of data science initiatives and company strategy
Lead projects and research initiatives
Develop algorithms and predictive models, create prototype systems, visualizations, and web applications
Design and analyze experiments
Assemble data sets from disparate sources and analyze using appropriate quantitative methodologies, computational frameworks and systems
Disseminate findings to non-technical audiences through a variety of media, including interactive visualizations, reports and presentations
Mentor junior team members Candidate Requirements:
Industry recognized expertise in actuary/underwriting domain
7+ years working with data and relevant computational frameworks and systems
7+ years developing of probabilistic models and machine learning algorithms
Proficient level of understanding in the following areas and an expert in at least one: machine learning, probability and statistics (esp. Bayesian methods), natural language processing, operations research
Exceptional problem solving skills and willingness to learn new concepts, methods, and technologies
Expert in data analysis using R or Python (numpy, scipy, matplotlib, scikit-learn, pandas, etc.) programming languages
Knowledge of NoSQL systems, Hadoop/map-reduce, Spark, Hbase, etc.
Experience in database design and SQL
Ability to work in a highly collaborative environment
Outstanding communication skills (publication history a plus) Education - M.S. or Ph.D. in a quantitative discipline (Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, etc.) is required
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