Director leading strategy, governance, and delivery of enterprise data platform at Phillips 66. Partnering with AI, Data Science, and business teams to enhance analytics and business systems.
About the role
- Data Scientist/Senior Data Engineer developing scalable data pipelines and machine learning models for finance transformation at Guardian. Collaborating across teams to enhance financial decision-making and operational efficiency.
Responsibilities
- Build and optimize large-scale data pipelines using PySpark, SQL, and Python
- Develop, deploy, and support predictive models and actuarial tools for financial reporting
- Automate manual actuarial/finance processes
- Collaborate with actuaries, finance SMEs, and business analysts to translate complex requirements into technical designs.
Requirements
- 6–8 years in a data engineering, actuarial modeling, or analytics-focused technical role
- 2+ years of hands-on ML modeling/development experience
- Strong programming skills in Python
- Solid understanding of data analysis and statistical modeling
- Experience with data wrangling including fuzzy matching and regular expression
- Working knowledge of Pricing and actuarial processes.
- Proficiency in Python, PySpark, and SQL is essential.
- Bachelor’s or Master’s degree in Computer Science, Actuarial Science, Mathematics, Engineering, Finance, or a related discipline or equivalent experience.
Benefits
- Support and flexibility to achieve professional and personal goals
- Skill-building opportunities
- Leadership development
- Philanthropic opportunities
- Opportunities to build communities and grow your career.
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