General Reinsurance (Gen Re) - Manager, Data Science Engineer

Paid / Remote / Full-time

At a high level, our team works on empowering Gen Re with modern, self-service data science tools and technologies and leading data science community-building efforts across the enterprise. Technologies include, for example, Posit professional products (Workbench, Connect, and Package Manager) and Azure cloud services related to data science, AI, and ML. Community-building includes internal R meetups and driving community discussion platforms.

Shape Your Future with Us

General Re Corporation, a subsidiary of Berkshire Hathaway Inc., is a holding company for global reinsurance and related operations,with more than 2,000 employees worldwide. Its direct reinsurance companies conduct business as Gen Re.

Gen Re delivers reinsurance solutions to the Life/Health and Property/Casualty insurance industries. Represented in all major reinsurance markets through a network of more than 40 offices, supported by over 2,000 employees worldwide, we have earned superior financial strength ratings from each of the major rating agencies.

Gen Re currently offers an excellent opportunity for a Manager, Data Science Engineer. This position can report into our Stamford, CT office, or can be performed remotely for an appropriately qualified individual within Global IT Services.

Role Description

The Manager, Data Science Engineer is a member of the Enterprise Data Services (EDS) team within Global IT Services.

In this capacity, the candidate will work with and manage a team of empathetic, autonomy-supported, well-connected, competent, and passionate data analysts, data engineers, data architects, and data scientists (i.e., a data team) responsible for empowering the organization with modern data science tools, technologies, and workflows.

The ideal candidate will be highly empathetic, collaborative, organized, analytical, and be expected to partner effectively with other business and service units.


  • Lead and enable a data team comprised of data analysts, data engineers, data architects, and data scientists to deliver on strategic data science objectives, initiatives, and projects.

  • Continue to build a highly collaborative, empathetic, and visible data science community.

  • Document organizational processes and procedures to ensure business efficiency and continuity.

  • Engage with stakeholders to communicate the vision for analytics platforms and systems, diplomatically overcome resistance to adoption, and communicate to business the value of data-centric solutions.

  • Recommend to business IT architectural patterns and solutions based on project goals and needs.

  • Meet routinely with business groups and stakeholders to learn about upcoming needs and challenges, as well as share data team updates (i.e., advocate for the tools we build and manage) and socialize upcoming changes.

  • Understand how new tools and technologies can fit alongside or within current tech stacks.

  • Collaborate with business and IT to define business problems, refine requirements, and design, develop, and deploy analytics systems and/or end-to-end solutions.

  • Identify ways to grow and mature our global data science and analytics platforms and environments.

  • Develop and maintain statistical programming standards and best practices to be advocated by IT and used by business.

  • Establish best practices on continuous integration and continuous deployment (CI/CD) pipelines.

  • Manage IT data science project pipelines. Prioritize initiatives and determine whether projects will be fulfilled by internal company teams or by other suppliers based on Gen Re capacity, skills, and urgency.

  • Promote the use of DevOps or MLOps in the delivery of solutions by internal and external development teams.

  • Develop organizational knowledge of key data sources and be a valuable resource to people in the company on how to best use data and analytics to pursue company objectives.

  • Plan and oversee the budget for the data science services vertical.

  • Stay informed about industry best practices in data and advanced analytics.

Role Qualifications and Experience

  • The ideal candidate will have a combination of IT skills, data governance skills, analytics skills, and insurance or re-insurance knowledge with an advanced technical or computer science background.

  • At least 7-10 years of work experience leading the designing, building, testing, and maintaining of analytics systems (e.g., RStudio/Posit).

  • At least 7-10 years of experience working in cross-functional teams and collaborating with business stakeholders in support of multi-departmental initiatives.

  • At least 5 years of experience applying and advocating DevOps to both IT and business units.

  • Strong experience with the Azure cloud, especially as it relates to supporting analytics-related services.

  • Advanced programming skills, such as debugging, data manipulation, analysis, visualization, and writing modular functions.

  • Advanced knowledge of analytics tools and systems and their associated trade-offs.

  • Experience with building custom analytics solutions.

  • Creative and innovative thinking.

  • Ability to network and be recognized as an expert in analytics systems across a variety of business and IT roles.

  • Ability to deliver high-quality work that has deadlines and competing priorities.

  • Ability to manage and supervise staff.

  • Excellent communication (verbal and writing) skills, including the ability to lead discussions, presentations, and training of technical and non-technical audiences.

  • Expert in the statistical programming language R and/or Python.

  • Strong experience with analytics tools such as RStudio/Posit and Power BI.

  • Strong experience with relational databases (e.g., MariaDB, Oracle) and/or non-relational databases.

  • Strong experience in producing reproducible work products.

  • Strong experience with dependency management.

  • Experience in iterative methodologies for development and capable of applying DevOps principles to data pipelines and analysis to improve the communication, integration, re-use, and automation of work products.

  • Working knowledge of modern predictive analytics, machine learning, or AI-based workflows.

  • Experience with implementing Actuarial concepts (e.g., pricing) into analytics systems.

  • Experience in governing third-party service delivery partners.

  • Experience with software development life cycle methodologies (e.g., Agile) and knowledge of current industry best practices for technology.

Salary Range

120,000.00 - 200,000.00 USD

The annual base salary range posted represents a broad range of salaries around the U.S. and is subject to many factors including but not limited to credentials, education, experience, geographic location, job responsibilities, performance, skills and/or training.

Apply to this position

1 Like

This topic was automatically closed after 31 days. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.