Data Scientist/ Senior Data Engineer – Finance Transformation

Is the opportunity to join a culture where “We Do the Right Thing,” and “We Courageously Shape Our Future Together” important to you? If so, Guardian is seeking a resolute motivated individual to join our team as a Data Scientist/Senior Data Engineer – Finance Transformation.

Guardian is seeking a technically skilled and business-savvy Technical Analyst / Data Engineer to design, develop, and support advanced actuarial and financial applications. This role will play a critical part in transforming our actuarial and finance functions by building scalable data pipelines, dashboards, and machine learning models that enhance decision-making and operational efficiency.

You will work closely with Actuarial, Finance, Data Science, and Technology teams to deliver solutions used in reserving, pricing, predictive analytics, and financial reporting.

You will:

• Machine Learning, Engineering & Analytics Development

  • Build and optimize large-scale data pipelines using PySpark, SQL, and Python on cloud platforms such as Databricks and AWS

  • Utilizing advanced statistical and AI/ML techniques to develop, deploy, and support predictive models and actuarial tools used for reserving, pricing, and FP&A (e.g., claims projection model, LTD Reserving model)

  • Automate manual actuarial/finance processes by integrating coding workflows with structured datasets and business logic

  • Support use case development that includes initial data exploration, project/sample design, reception, and processing of data, performing analysis and modeling to creation of final report/presentation

  • Data wrangling/data matching/ETL to explore a variety of data sources, gain data expertise, perform summary analyses, and prepare modeling datasets

  • Identification of source data and data quality checks both in model/solution development and in production

  • Packaging of model/solution and deployment in cooperation with Data Engineers and MLOps

  • Implement new statistical or other mathematical methodologies as needed for specific models or analysis.

• Data Integration & Validation

  • Work across data domains to ingest, cleanse, and structure financial and actuarial datasets from multiple sources (e.g., Claims systems, Billing and Commissions system)

  • Implement robust data quality checks and reconciliation controls to ensure accuracy and completeness of critical reporting and modeling datasets

• Collaboration & Documentation

  • Collaborate with actuaries, finance SMEs, and business analysts to translate complex requirements into efficient technical designs.

  • Maintain clear documentation for code, data flows, model logic, and user instructions.

You have

• Technical Expertise & Domain Knowledge

  • 6–8 years in a data engineering, actuarial modeling, or analytics-focused technical role, ideally in Group insurance or Financial services

  • 2+ years of hands-on ML modeling/development experience

  • Solid understanding of data analysis and statistical modeling.

  • Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks.

  • Demonstrated track records in experimental design and executions

  • Hands-on experience with data wrangling including fuzzy matching and regular expression, distributed computing and applying parallelism to ML solutions

  • Strong programming skills in Python

  • Solid background in algorithms and a range of ML models

  • Working knowledge of Pricing and actuarial processes, or Group insurance product structures

  • Proficiency in Python, PySpark, and SQL is essential

  • Experience working with Databricks, Tableau, Power BI, or similar visualization and cloud platform

  • Exposure to ML/AI libraries and framework to develop or enhance models

• Soft Skills

  • Analytical mindset with strong attention to detail

  • Self-starter who thrives in fast-paced, cross-functional teams

• Education

  • Bachelor’s or Master’s degree in Computer Science, Actuarial Science, Mathematics, Engineering, Finance, or a related discipline or equivalent experience.

• Preferred Qualifications

  • Hands-on experience building valuation, reserving, or pricing models for group insurance products

  • Experience in agile or SAFe environments with sprint planning, Jira, or Confluence

  • Strategic and creative thinker with ability