Sr. Data Scientist

Key Skills

Bayesian networks, Data science techniques, Decision trees, Effective communication skills, Linear Models, Machine learning techniques, Multivariate analysis, Non Linear Programming, Python Programming, R Programming, SAS, Software Development, SQL

Job Description

The Senior Data Scientists will take a lead role in the end-to-end process of data science initiatives with limited supervision, including but not limited to model design, structure, development and post-deployment model performance monitoring. By conducting innovative research through advanced analytics and technical sophistication, the Senior Data Scientist will contribute to create the economic value at scale from both future growth and profitability perspectives. 

In this role, you will be set on a constant “treasure hunt for new data sources to apply the latest techniques for modeling projects. You will have unparalleled opportunity to apply state-of-the-art machine learning techniques to real world datasets. You will work on a team of PhD level statisticians to create ground-breaking predictive models using new analytical techniques that determine insurance pure premiums, customer life time value, customer buying behaviors and other related topics. This work will be used in setting pricing, underwriting, marketing, policy and claims service, fraud detection and product design strategies for the Plymouth Rock group of Companies. The role is not simply research: you will be part of a tactical team driving the profit and customer growth of an assigned business segment. The analysis and modeling will be tested via implementation both broadly and on a pilot basis to allow us to learn and refine our approaches in rapid succession.

Education Requirement and Qualification

• PhD from a quantitative area such as STEM (Science, Technology, Engineering and Mathematics), Economics, and Business.
• 5+ years of data science experience of developing and deploying advanced solutions with innovated concepts and sophisticated methodologies in the areas of Finance, IRM (Insurance and Risk Management), and Actuarial Science.
• Hands-on modeling experience and deep understanding of both conventional quantitative analytics such as GLM, GLMM, Bayesian statistics, Actuarial methods and tree-based machine learning techniques like GBM, Random Forest, Topics Model and Deep Learnings.
• Excellent programming skill of major software packages such as Python, R and SAS
• Deep understanding of database principle and solution deployment platform.
• Excellent communication skills both written and oral.
• Self-starter and critical thinking

Essential Functions and Education

• Heavily contribute to the end-to-end predictive solution provision process, which includes but not limited to, technical evaluation of data usage, methodological selection, model development and creation/maintenance of post-deployment monitoring capability.
• Actively participate the feedback loop among different stakeholder groups to address newly emerging issues in a timely and constructive manner
• Collaborate with upper management to evaluate the impact of proposed solutions and incorporates these considerations into recommendations. 
• Work with third party vendors and leading research institutions to explore new data source and newer methodologies seeking continuous improvement.
• Data Science projects include but not limited to development of pricing models, evaluation of customers’ lift time value, credibility methodologies as well as experiment/algorithm design and implementation on Telematics.
• Communicate analytics, strategy and recommendations to diverse audiences, including technical and non-technical.
• Manage working streams of high complexity.
• Perform other job-related duties as assigned.