Lead Data Scientist and Engineer

6 days ago


IL United States The Hartford Financial Services Group Full time
About the Role

The Hartford Financial Services Group is seeking a highly skilled Director of Data Science and Engineering to lead our Language AI Enablement team. As a key member of our organization, you will be responsible for developing and implementing cutting-edge Natural Language Processing (NLP) and Generative AI solutions to drive business growth and improve customer experiences.

Key Responsibilities
  • Team Leadership: Manage a team of Data Scientists and Data Engineers to design, develop, and deploy robust data solutions using unsupervised techniques.
  • Upskilling and Development: Support the upskilling journeys of team members, collaborating closely with stakeholders to identify areas for growth and development.
  • Best Practices and Research: Evolve best practices in NLP and Gen AI, guiding the direction of our Data Science community and staying current on research techniques and state-of-the-art tools.
  • Cross-Functional Projects: Lead or support cross-functional projects with expertise to achieve financial objectives, solve business problems, and identify long-term opportunities that improve the customer journey.
  • Department Advancement: Advance the department's capabilities by creating and deploying long-term tools to continually evolve the practice of data science, with an ability to see the end-to-end solution.
  • Communication and Collaboration: Collaborate and partner with data science and business stakeholders to support the vision and sustain a culture that treats analytics as a corporate asset, communicating effectively with both technical and non-technical teams.
  • Talent Management: Participate in the talent management process for hiring, onboarding, training, and development of staff.
Qualifications
  • Experience: 8+ years of relevant experience recommended.
  • Education: Master's or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or progress towards a relevant professional designation.
  • Expertise: Experience with managing Data Scientists and Data Engineers, statistical modeling, inference, and building machine learning algorithms in Python, Unix, Git, and cloud-native environments such as Sagemaker.
  • Soft Skills: Ability to translate complex technical topics into business solutions and strategies, and turn business requirements into a technical solution.

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