Data Analytics Officiator, Individual Markets

Data Analytics Officiator, Individual Markets

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. We've recently onboarded a Chief Data & Analytics Officer (CDAO) to guide this transformation and lead the Enterprise Data and Analytic Office (EDAO). This role presents a distinctive opportunity to collaborate with the CDAO and the Head of Data Science, Individual Markets, actively giving to Guardian’s ongoing evolution.

Guardian’s EDAO spearheads a culture of data insights across Guardian, facilitating the successful realization of our strategic initiatives. Our core activities encompass creating business value from our data and analytic products. Key responsibilities include data lifecycle management, insight development, and data product delivery. We are a team of data analysts, data product owners, data engineers, data scientists and most importantly, data business leaders. Our solutions and actions are critical to Guardian’s revenue growth, risk management and customer experience.

Guardian is seeking experienced leader with a solid background in production ready data analytics solutions. In this role, you'll be working in a team of Data Analysts/Scientists to develop advanced analytical/data science solutions, leveraging data, information, 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 Analysis, Data Science, Data Engineering, and Business groups. Successful candidates have strong technical foundation, excel in coding, detail oriented, and have passion for analytical thinking and problem solving.

You Are:

• You are passionate about innovative technology and keen on applying new AI/ML algorithms and approaches.
• You are analytically driven, intellectually curious, and experienced leading the development and implementation of data and analytic solutions to solve ambitious business problems.
• You enjoy collaborating with other data scientists to crack hard to solve problems with AI/ML and seeing it deployed in-market and generating value for Guardian.
•  You enjoy collaborating with a multi-disciplinary team including data engineers, business analysts, software developers and functional business authorities and business leaders.

You Will:

• Manage solutions analytical to business problems
• 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
• Applying advanced statistical and AI/ML techniques to create hard-working 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 collaboration 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

You Have:

• PhD with 6+ years of experience, Master's degree with 10+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field
• 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 sk