Senior Data Scientist, AI Studio

Guardian Life Insurance•Boston, MA

2d•Hybrid

About The Position

Guardian is on a transformation journey to evolve into a modern, forward-thinking insurance company committed to enhancing the wellbeing of its customers and their families. This role presents a distinctive opportunity to drive real-world impact by applying cutting-edge AI to transform how Guardian does business. Guardian’s AI team spearheads a culture of intelligence and automation across the enterprise, creating business value from advanced data and AI solutions. Our team includes data scientists, engineers, analysts, and product leaders working together to deliver AI-driven products that power growth, improve risk management, and elevate customer experience. Guardian is seeking experienced individual contributor with a strong background in production ready AI/ML solutions. In this role as Senior Data Scientist, you'll be working in a team of Data Scientists led by Lead Data Scientist to develop advanced data science solutions, leveraging machine learning and artificial intelligence, to drive enterprise-wide innovation across various business lines and Guardian products. You'll collaborate with cross-functional teams of other Data Science, Data Engineering, Business groups. Successful candidates have strong technical foundation, excel in coding, detail oriented, and have passion for analytical thinking and problem solving.

Requirements

PhD with 2+ years of experience, Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field
3+ years of hands-on ML modeling/development experience
Solid understanding of data analysis and statistical modeling.
Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks.
Demonstrated track records in experimental design and executions
Hands-on experience with data wrangling including fuzzy matching and regular expression, distributed computing and applying parallelism to ML solutions
Strong programming skills in Python
Solid background in algorithms and a range of ML models
Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level
Excellent analytical and problem-solving abilities with superb attention to detail
Proven leadership in providing technical leadership and mentoring to data scientists and strong management skills with ability to monitor/track performance for enterprise success
In order to be a successful applicant. you must be legally authorized to work in the United States, without the need for employer sponsorship.

Responsibilities

Lead use case/workstream with junior data scientists
Support use case development that includes initial data exploration, project/sample design, reception and processing of data, performing analysis and modeling to creation of final report/presentation
Data wrangling/data matching/ETL to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets
Utilizing advanced statistical and AI/ML techniques to create high-performing predictive models and creative analyses to address business objectives and partner needs
Identification of source data and data quality checks both in model/solution development and in production
Packaging of model/solution and deployment in cooperation with Data Engineers and MLOps
Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
Propose innovative ways to look at problems through using data mining and data visualization
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Present information using data visualization techniques; communicate results and ideas to key decision makers.
Ensure data accuracy and consistent reporting by performing regular data quality control, prepare and maintain reports, and troubleshoot data anomalies
Consistent accuracy and thoroughness in performing work assignments
Attend industry conferences to stay current on industry trends, challenges, and potential market opportunities
Contribute to standardization of Data Science tools, processes, and best practices