Description
As a Principal Data Scientist, you will be an individual contributor and senior technical leader supporting multiple teams, driving innovation in data science, infrastructure, and product development.
You will play a strategic role in shaping our advanced product roadmap, building scalable ML workflows, and collaborating across disciplines to deliver data-driven solutions that support our business goals.
Responsibilities:
- Explore Generative AI or machine learning product solutions developed by US colleagues and apply them to the local business.
- Proactively explore other AI solutions to identify and assess their viability in enhancing current operations.
- Act as a data science expert, contributing to and guiding multiple projects across domains.
- Support cloud migration, collaborating with technology teams to ensure analytics infrastructure aligns with long-term goals.
- Develop and prototype innovative solutions through infrastructure to improve accuracy, efficiency, and productivity.
- Build Predictive models for the insurance industry to test products and add embedding layers for enhanced predictive capabilities.
- Build and deploy new data products, including ETL pipelines and statistical models, in collaboration with technology teams.
- Collaborate with stakeholders across product, technology, and data engineering to align priorities and vision.
- Communicate complex analytical results clearly and effectively to both technical and non-technical audiences.
- Mentor team members and contribute to a culture of technical excellence and continuous learning.
Requirements:
- Degree in Mathematics, Statistics, Physics, Computer Science, or a related quantitative field; advanced degree preferred.
- 8+ years of experience in data science or a related field.
- Strong programming skills in Python or R, with experience in Azure ML Flow and/or Apache Spark and distributed computing.
- 3+ years of industry experience with mathematical modelling, building predictive models, and implementing them into a production environment.
- Expertise in data processing, including extraction, cleaning, transformation, and handling diverse formats.
- Experience building robust, testable data pipelines and writing clean, maintainable code.
- Strong SQL skills and familiarity with relational and non-relational databases.
- Proven ability to interpret, report, and present data with a focus on consistency, integrity, and business value.
- Excellent communication skills, with the ability to present findings to varied audiences.
- Experience mentoring others and leading technical workstreams.
- Experience with version control (Git), documentation standards, and collaborative development practices.