Data Science Intern at Hearst Newspapers tackling real - world challenges in digital media. Collaborating with teams to derive insights and influence business strategies.
About the role
- Director of Data Science leading a team to develop AI solutions in The Hartford's Claims & Operations. Focusing on machine learning and data analytics across policy and claim lifecycles.
Responsibilities
- Manage a team of Data Scientists to develop, test, validate, and maintain robust tools using supervised and, unsupervised, and generative techniques
- Lead cross-functional projects that include the creation of AI workflows, statistical models, algorithms, and machine learning techniques to achieve financial objectives, solve business problems, and identify long-term opportunities that improve the customer journey
- Collaborate and partner with business stakeholders in a way that supports the vision and sustains a culture that treats analytics as a corporate asset
- 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
- Develop strategies to achieve targeted business objectives. Implement these strategies and follow through to successful conclusion
- Remain current on research techniques and become familiar with state-of-the-art tools applicable to your function
- Participate in the talent management process for hiring, onboarding, training and development of staff
- Collaborate with your leader to provide timely feedback on development and opportunities for your team
- Learn/bring best practices to guide the direction of our Data Science and Data Engineering workflows
Requirements
- 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, or progress towards a relevant professional designation
- Experience with managing Data Scientists and providing guidance through model development
- Expertise in statistical modeling, inference, and building machine learning algorithms in Python
- Experience in leveraging Generative Artificial Intelligence (e.g., large language, image generation, & multimodal generative models) including model selection & tuning, prompt engineering, and performance evaluation
- Expertise in SQL and navigating databases to extract relevant attributes
- Expertise in Unix and Git
- Expertise in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation
- Experience building modeling solutions in cloud-native environments, such as Sagemaker, a plus
- Able to communicate effectively with both technical and non-technical teams
- Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution
- Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques
- Candidate must be authorized to work in the US without company sponsorship.
Benefits
- Other rewards may include short-term or annual bonuses
- Long-term incentives
- On-the-spot recognition
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