Data Scientist/ Senior Data Engineer – Finance Transformation

Guardian Life InsuranceHolmdel Township, NJ
1dHybrid

About The Position

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.

Requirements

  • 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
  • Analytical mindset with strong attention to detail
  • Self-starter who thrives in fast-paced, cross-functional teams
  • Bachelor’s or Master’s degree in Computer Science, Actuarial Science, Mathematics, Engineering, Finance, or a related discipline or equivalent experience.

Nice To Haves

  • 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 to think outside the box and translate strategies into actions
  • Excellent problem-solving skills
  • Team player with proven ability to foster and manage working relationships within a matrix environment
  • Candidate must be comfortable with ambiguity in strategic direction. Priorities will change as current uncertainties become new standards and shape the market. There must be constant balance between proactive and reactive strategy and execution.
  • Candidate must work well in a collaborative and diverse team environment, understanding and employing the approach and standard operating procedures of all functional areas across Guardian
  • Excellent oral and written communication skills

Responsibilities

  • 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.
  • 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
  • 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.

Benefits

  • At Guardian, you’ll have the support and flexibility to achieve your professional and personal goals.
  • Through skill-building, leadership development and philanthropic opportunities, we provide opportunities to build communities and grow your career, surrounded by diverse colleagues with high ethical standards.
  • As part of Guardian’s Purpose – to inspire well-being – we are committed to offering contemporary, supportive, flexible, and inclusive benefits and resources to our colleagues.
  • Explore our company benefits at www.guardianlife.com/careers/corporate/benefits.
  • Benefits apply to full-time eligible employees.
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