Senior Data Scientist Reinforcement Learning
Senior Data Scientist Reinforcement Learning
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Job Description
Chubb is a world leader in insurance. With operations in 54 countries Chubb provides commercial and personal property and casualty insurance personal accident and supplemental health insurance reinsurance and life insurance to a diverse group of clients. The company is distinguished by its extensive product and service offerings broad distribution capabilities exceptional financial strength underwriting excellence superior claims handling expertise and local operations globally.
Key Objectives:
Chubbs Global Analytics Team is seeking an experienced and dynamic Reinforcement Learning expert to join our vibrant and fastpaced environment dedicated to pioneering innovative AI solutions. This role is an individual contributor as the ideal candidate will be integral in developing and overseeing the delivery of highquality RL based AI products.
To succeed in this role you should be a resourceful problem solver with a strong sense of ownership and a commitment to excellence. A true team player youll think holistically and approach challenges with a foundational mindset seeking opportunities for simplification and improvement. You will prioritize iterative value delivery adeptly managing and embracing the inherent uncertainties that accompany the fastevolving landscape of AI research and application.
Major Responsibilities:
- Drive the design development and deployment of Reinforcement Learning focused AI products ensuring alignment with business objectives.
- Research & implement cuttingedge modeling techniques focused on Deep Learning and Reinforcement Learning.
- Conduct rigorous feature engineering offline model evaluation and online A/B testing of model performance
- Guarantee the delivery of highquality code that aligns with business objectives adheres to quality standards and complies with secure web development practices.
- Manage project timelines and milestones ensuring timely delivery of AI initiatives while maintaining quality and performance standards.
- Ensure high quality code that meets business objectives quality standards and secure web development guidelines.
- Manage project stakeholder expectations and issue communications on progress.
- React to shifting priorities without compromising deadlines and momentum.
Qualifications
Must have:
- Masters or PhD in Computer Science Computer Engineering or related field.
- At least 5 years of experience in Deep Learning and Reinforcement Learning with significant expertise in writing and reviewing production code in Python.
- Solid understanding of Reinforcement Learning theory including (but not limited to) Markov Decision Process value iteration policy optimization and explorationexploitation tradeoffs.
- Proficient in ML frameworks and libraries (e.g. PyTorch) and knowledgeable about various ML techniques and their largescale implementation in production environments.
- Experience developing software using major container technologies (e.g. Kubernetes Docker) and familiarity with Continuous Integration tools.
- Ability to work independently and work as a team member with excellent communication skills and mentorship abilities.
Nice to have:
- Experience in designing data pipelines is a significant advantage.
- Familiarity with endtoend application development using a full stack is a plus.
- Knowledge of property and casualty (P&C) insurance is a valuable asset.
At Chubb we are committed to providing equal employment opportunities to all employees and applicants. It is our policy to provide equal employment opportunities to employees and applicants based on jobrelated qualifications and ability to perform a job. If you require accommodation during the hiring process or upon hire please inform Human Resources. If a selected applicant requests accommodation during the recruitment process Chubb will consult with the applicant in order to provide suitable accommodation that takes into account the applicants accessibility needs.
Required Experience:
Senior IC
Employment Type
Full-Time
