Apply on Employer Site

Guardian Life · 1 week ago

Data Scientist/ Senior Data Engineer – Finance Transformation

Bethlehem, PA

Full-time

Hybrid

Mid, Senior Level

$99K/yr - $163K/yr

6+ years exp

Guardian Life is seeking a resolute motivated individual to join their team as a Senior Data Engineer – Finance Transformation. This role will play a critical part in transforming their actuarial and finance functions by building scalable data pipelines, dashboards, and machine learning models that enhance decision-making and operational efficiency.

DentalFinancial ServicesHardwareInsuranceLife Insurance

No H1B

U.S. Citizen Only

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

Qualification

Machine LearningData EngineeringPythonSQLPySparkDatabricksStatistical ModelingAnalytical MindsetCollaborationProblem-SolvingCommunication Skills

Required

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

Preferred

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