Resolution Life US is looking to become a data-driven, AI-enabled company obsessed with improving customer outcomes. This role will drive the technology pillar of RLUS strategy to achieve this goal.
Requirements
- 6+ years of experience in data science or AI roles, with at least 2 years in a leadership position.
- Demonstrated experience in deploying AI solutions into production environments.
- Familiarity with MLOps practices and deploying models to production environments.
- Proficiency in Python, including libraries such as pandas, scikit-learn, numpy, and matplotlib.
- Strong understanding of graph databases (e.g., Neo4j) and graph algorithms.
- Experience with large language models and natural language processing techniques.
- Familiarity with Jupyter notebooks, Git, and APIs.
Responsibilities
- Lead the design, development, and deployment of AI solutions, ensuring scalability and robustness.
- Mentor and guide a team of data scientists and engineers, fostering a culture of continuous learning and innovation.
- Collaborate with cross-functional teams, including actuaries, product managers, and cloud engineers, to integrate AI tools into existing workflows and systems.
- Drive the exploration and implementation of graph-based algorithms and LLMs to solve complex business problems.
- Ensure best practices in MLOps are followed for efficient model deployment and monitoring.
- Stay current on emerging tools in the GenAI and machine learning ecosystem (e.g., LangChain, Hugging Face, vector databases, etc.).
- Explore and evaluate emerging technologies (e.g., neuromorphic computing, edge AI, quantum ML) that have the potential to transform the industry over the next 3–5 years.
Other
- Highly motivated and experienced Technical Lead
- 6+ years of post-university experience
- Strong communication skills and ability to work collaboratively in a hybrid or remote team environment.
- Experience working in startup environments, demonstrating adaptability and a proactive approach to problem-solving and comfort with ambiguity in fast-paced innovation settings.
- Proficiency in Japanese is preferred, though not a requirement.
