Data Engineer

4 weeks ago

Hartford, United States The Hartford Full time

Data Engineer - GE08AE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

The Hartford is seeking a Data Engineer within Actuarial Technology to design, develop, and implement modern and sustainable data assets to fuel machine learning and statistical modeling solutions across a wide range of strategic initiatives.

This role will have a Hybrid work arrangement, with the expectation of working in an office (Hartford, CT & Charlotte, NC) 3 days a week (Tuesday through Thursday).

The Actuarial Technology team is a dynamic mix of Actuarial, Data Science and Engineering professionals utilizing statistical modeling, machine learning, and advanced data engineering techniques to enhance core Actuarial processes. As a member of the Middle and Large Commercial Lines pillar, you will directly impact written premium by ensuring the modeling team can find new insights and deliver them to market rapidly. We are a forward-focused organization that fosters collaboration, encourages creative design, and offers abundant opportunities for visibility, allowing candidates to shape innovative solutions and showcase their talents to a wide audience.

As a Data Engineer, you will be at the forefront of driving impactful solutions throughout the entire software development lifecycle, ensuring reliable data delivery. Collaborating closely with a team of talented engineers and data scientists, you will play a pivotal role in meeting the evolving needs of our Actuarial modelers, enabling our collective success. Our team's culture is deeply rooted in embracing emerging technologies and empowering you to select the optimal tools for each unique project, so curiosity and adaptability are highly valued. On this team, you will gain experience with modern data technology, agile software engineering practices, MLOps, and business-driven process design. Strong candidates will demonstrate a solid foundation in data management and software development along with an enthusiasm for learning the insurance business and delivering efficient solutions to partners.

Responsibilities:

  • Develop high quality, scalable software modules for next generation analytics solution suite that serves advanced statistical models and track key metrics
  • Create data assets and build data pipelines that align to modern software development principles for further analytical consumption.
  • Perform preliminary exploratory analysis to evaluate nulls, duplicates and other issues with data sources.
  • Build automated data pipelines with Airflow and MLflow that serve advanced statistical models and track key metrics.
  • Enhance and maintain model and data monitoring solutions that deliver automated insights to technical and non-technical audiences
  • Consult with cross-functional team partners to understand business needs and develop reliable and effective solutions, that are easily maintainable
  • Engage in activities with cross-functional IT unit stakeholders (e.g., database, operations, telecommunications, technical support, etc.)
  • Contribute to engineering projects, leveraging agile software development practices to manage work and communicate status
  • Prototype high impact innovations that advance the Data Engineering capabilities of the Actuarial department, by leveraging new technologies (AWS, MLOps and Big Data).
  • Proactively accesses technical issues and risks that could impact speed, functionality, flexibility, or clarity.
  • Use Enterprise GitHub for version control, documentation, code collaboration, and technical project management
  • Manage data and project work in a Linux-based filesystem.
  • Support Actuarial community enablement efforts, including solution implementation and best practices adoption, through documentation, hands on instruction and formal training.
  • Regularly engage in continuing education, including the development of MLOps and Cloud Engineering skills as well as Insurance Business proficiency
Minimum Qualifications:
  • 2+ years programming experience in a business setting.
  • Proficiency in SQL and at least one additional functional or object-oriented programming language such as R or Python
  • Demonstrated history of manipulating and extracting value from various data structures and databases.
  • Ability to communicate effectively with both technical and non-technical teams
  • Interest in deeply learning & understanding the Insurance Business and Actuarial role
  • Curious and passionate for R&D and innovation
Preferred Skills and Experience:
  • Experience using GitHub for version control strongly preferred
  • Exposure to Machine Learning, Statistical Modeling, or MLOps in a business context is preferred
  • Experience with AWS or similar cloud computing platform is preferred
  • Experience with Insurance data, especially with Pricing data processes, is a strong plus
  • Exposure to Automation tools (Airflow, Cron, Autosys, etc.) is a plus
  • Experience with agile software development is a plus
  • Exposure to containerized computing (Docker, Kubernetes, etc.) is a plus
  • Any AWS Cloud certification is a plus
  • Experience with Linux-based file management desired

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us | Culture & Employee Insights | Diversity, Equity and Inclusion | Benefits

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