Data Science Director

2 days ago

Chicago, Illinois, United States The Hartford Financial Services Group Full time
Job Description

The Hartford Financial Services Group is seeking a highly skilled Director of Data Science to lead a team of Data Scientists and Data Engineers in the Language AI Enablement team. The successful candidate will have a strong background in statistical modeling, machine learning, and data engineering, with experience in managing teams and developing innovative solutions.

Key Responsibilities:

  • Manage a team of Data Scientists and Data Engineers to develop, test, and maintain robust tools using unsupervised techniques.
  • Support upskilling journeys tailored to the needs of the team and partners.
  • Evolve best practices in the NLP and Gen AI space to guide the direction of the Data Science community.
  • Lead or support cross-functional projects with expertise to achieve financial objectives, solve business problems, and identify long-term opportunities.
  • Remain current on research techniques and become familiar with state-of-the-art tools applicable to the function.
  • Advance the department's capabilities by creating and deploying long-term tools to continually evolve the practice of data science.
  • Collaborate and partner with data science and business stakeholders to support the vision and sustain a culture that treats analytics as a corporate asset.
  • Develop strategies to achieve targeted business objectives and implement these strategies to successful conclusion.
  • Participate in the talent management process for hiring, onboarding, training, and development of staff.

Qualifications:

  • 8+ years of relevant experience recommended.
  • Master's or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field.
  • Experience with managing Data Scientists and Data Engineers and providing guidance through solution development.
  • Expertise in statistical modeling, inference, and building machine learning algorithms in Python.
  • Expertise in Unix and Git.
  • Expertise in the end-to-end solution lifecycle, from requirements gathering to monitoring and validation.
  • Experience building solutions in cloud-native environments, such as Sagemaker.
  • Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution.
  • Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning is a plus.
  • Experience with NLP or CV is a plus.

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