Senior Advisor for Technology Strategy

This is your opportunity to join AXIS Capital – a trusted global provider of specialty lines insurance and reinsurance.  We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders. We also proudly maintain an entrepreneurial, disciplined and ethical corporate culture.  As a member of AXIS, you join a team that is among the best in the industry.

At AXIS, we believe that we are only as strong as our people. We strive to create an inclusive and welcoming culture where employees of all backgrounds and from all walks of life feel comfortable and empowered to be themselves. This means that we bring our whole selves to work. 

All qualified applicants will receive consideration for employment without regard to race, color, religion or creed, sex, pregnancy, sexual orientation, gender identity or expression, national origin or ancestry, citizenship, physical or mental disability, age, marital status, civil union status, family or parental status, or any other characteristic protected by law. Accommodation is available upon request for candidates taking part in the selection process.

Job Description

Data and analytics are of critical importance for AXIS. This role serves as the point person and leader of an organization responsible for delivery and engineering of Data and Analytics capabilities. The role is required to manage and mentor a team of data engineers. Hybrid: 3 days a week.
 

Responsibilities

• Supervising end-to-end BTS delivery for data and analytics projects, managing delivery and maintenance budgets, optimizing resource utilization, and tracking project KPIs.
• Review the existing data estate as well as elements of the data integration/transport architecture that lie within BTS. Further, assist in the design and validation of the long-term data estate, ensuring alignment with governance and compliance standards.
• Overseeing data and analytics technologies, collaborating with technical teams to select suitable tools, platforms, and frameworks in support of long-term analytics goals.
• Staying informed about industry trends and developments in data management and analytics. Keeping up to date with the latest advancements in the field.
• Driving and facilitating development and deployment of application-level changes via application delivery teams to accomplish improved data capture and data quality.
• Facilitating migration of data science and other D&A deliverables to production IT environments via application delivery teams.
• Owning and improving day-to-day operational aspects (robustness, resiliency, performance) of data integration, ETL, and related data transport elements.

Qualifications

• Have a deep understanding of insurance industry trends and best practices in data and analytics, particularly in data standards (e.g. ACORD) and experience in predictive modelling and risk assessment techniques.
• Be familiar with big data and cloud platforms such as Hadoop, Spark or Kafka and AWS, Azure, Google Cloud. Excellent knowledge of database management systems such as SQL Server, Oracle or MySQL is also essential.
• Have knowledge of machine learning frameworks and tools such as TensorFlow, PyTorch or Scikit-learn.
• Have proficiency with programming and visualization tools such as Python, R, or SQL; Tableau, Power BI or Looker.
• Possess technical familiarity in data warehousing tools such as DataBricks, Redshift, BigQuery, or Snowflake. Additionally have expertise in data integration tools such as Apache, NiFi, Talend or Informatica

Skills & Attributes

• Have a proven track record of developing and implementing data and analytics solutions while demonstrating a continuous improvement mindset.
• Possess a relevant background in data science, computer science, or a related field.
• Possess exceptional leadership skills and extensive experience in leading data and analytics delivery and engineering functions.
• Demonstrate strategic thinking and ability to align data initiatives with business goals
• Possess excellent communication and collaboration skills, including being able to communicate complex data concepts to non-technical stakeholders.