Principal Data Scientist, Cloud (REMOTE)

We are looking for a Principal Data Scientist to join the Insurance Analytics team to execute analytics team migrations to the cloud and drive adoption. This individual is responsible for managing data, applications and services analytics teams use for model development and deployment, batch processing and other analytics workflows. The ideal candidate has a strong sense of ownership, sense of urgency and be able to clearly communicate effectively to technical audiences and to senior leadership on key milestones and has solid expertise in cloud migration approaches.

Responsibilities:

• Develop a comprehensive data and analytics cloud migration strategy as part of a broader technology modernization and migration to Microsoft Azure.
• Drive thought leadership and execution of cross-functional analytics teams to enable adoption of data processing and analytical infrastructure in the cloud.
• Manage, optimize, and operationalize data lakes, data science virtual machines and other DevOps tools (Github, Jfrog) to enable faster go-to-market capabilities for data science teams.
• Architect and build core components of machine learning and data engineering platform infrastructure.
• Develop a comprehensive user, developer, manager education program to accelerate onboarding into a governed self-service data ecosystem.
• Define, manage and report out operational SLAs and KPIs for data platforms and solutions
• Partner with data science and IT engineering teams to high performance, efficient feature pipelines from backend proprietary data
• Simplify the technology stack to sunset legacy applications while minimizing business disruptions.
• Experienced in diagnosing, isolating, and resolving complex issues and recommending and implementing.
• Experienced in identifying operational issues, recommending, and implementing strategies to resolve them.
• Experienced in managing cross-functional and matrix teams.
• Experienced influencing leadership and key stakeholders on technology solutions
• Specific experience in cloud-based data solutions such as Azure BLOB or ADLS and Synapse, AWS S3, EMR and Redshift, Databricks, Snowflake, etc.
• Demonstrated experience with the lifecycle management of enterprise-class data platforms, including large-scale data migrations.
• Ability to lead user research to simplify and improve the development process for analytics.
• Demonstrated experience with implementing solutions to monitor and improve data availability across multiple domains.
  
  

Basic Qualifications:

• Degree (Bachelor’s) in Engineering, Computer Science, Data Science or a Quantitative field
• 10+ years of hands-on experience with data science/machine learning models using on-prem or cloud architectures
• 5+ years of ETL, data engineering and data pipeline development process SQL or other database management tool
• Exposure to Linux and Windows server including support and troubleshooting.
• Strong verbal and written communications skills, program/project management skills and exposure to DevOps tools
• Is comfortable presenting to large data science teams, technology teams and business and analytics leadership teams.
  
  

Preferred Qualifications:

• Master's degree in a relevant field and 5+ years of relevant work experience
• Or a PhD in a relevant field with 2+ years of relevant work experience
• Data Science/Machine Learning Cloud Certification (AWS, Azure, Google)
• Domain expertise in analytics solution architecture (DSVMs, Databricks, Data lake Gen 2, Jfrog, Github, Airflow)
• Built and deployed machine learning models in the Cloud (Azure ML Studio, AWS Sagemaker) and experience in building data/ETL pipelines
• Has strong presentation skills and has presented to large data science teams, technology teams and business and analytics leadership teams.