Data Scientist leading advanced ML and AI solutions at Vibra Energia. Responsible for data capabilities and automation impacting business outcomes.
About the role
- Senior Data Scientist for The Hartford developing machine learning solutions for actuarial pricing and underwriting. Collaborating with teams to enhance the policy lifecycle for Employee Benefits customers.
Responsibilities
- Create 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 and sustains a culture that treats analytics as a corporate asset
- Partner with Actuarial and Data teams to monitor and manage the End-to-End lifecycle of the rating models and underlying data which feeds them
- Lead execution of modeling and machine learning projects that focus on internal team collaboration with Data Scientists, Data Engineers, and Product Owners
- Assist in identifying and assessing the value of new data sources and analytical techniques to ensure ongoing competitive advantage
- Contribute to successful implementation of strategies to achieve targeted business objectives
- Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources in your area of expertise
- Remain current on research techniques and become familiar with state-of-the-art tools in generative AI
- Provide economic, qualitative, and statistical support to ensure accuracy of characteristics and metrics being applied to business decisions
- Learn/bring best practices to guide the direction of our Data Science and Data Engineering workflows
Requirements
- 5 + years of relevant industry 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
- Proficiency in statistical modeling , inference , and building machine learning algorithms in Python
- Proficiency in SQL and navigating databases to extract relevant attributes
- Proficiency in Unix and Git
- Proficiency in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation
- Experience building modeling solutions in cloud-native environment s , such as Sage M aker, 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.
- The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
Benefits
- Other rewards may include short-term or annual bonuses
- long-term incentives
- on-the-spot recognition
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