This role pays less than
71%
of similar roles. Most pay
$128,232–$208,925
— the shaded band above.
At the midpoint, this role pays about
$139k
versus about
$169k
for comparable roles.
Based on 240 similar postings.
Employer
About Genworth Financial
Genworth Financial is a financial services company focused on mortgage insurance, long-term care insurance, and life insurance and annuity products to help people protect their financial well-being. Industry: Insurance & Financial Services
Genworth Financial currently has
24 open roles
on FindRole.
Listed pay typically runs
$120,900–$187,000
across 24 roles with salary data.
The Data Scientist Manager serves as both a strategic thought partner and technical expert driving advanced analytics capabilities across the organization. You will lead complex, cross-functional initiatives from concept to execution, partnering with senior leaders to translate business needs into data-driven solutions for Long-Term Care Insurance strategy. Day-to-day responsibilities include developing advanced statistical models, machine learning tools, predictive capabilities, and repeatable analytics pipelines while ensuring model documentation and governance standards are met. You will build analytical assets using SQL, SAS, Python, R, Apache Spark, Hive, and Scala within cloud environments. Required skills include expertise in logistic regression, time series, forecasting, optimization, GLMs, and XGBoost. The role focuses on solving problems related to policy behavior, claims processes, and data modernization projects to improve customer insights and organizational analytic maturity.
Lead complex, cross-functional analytics initiatives from initial concept through final execution to drive business strategy.
Partner with senior leaders to define analytical problem statements and translate business needs into technical requirements.
Develop and deploy advanced statistical models, machine learning tools, and predictive capabilities for long-term care insurance.
Conduct deep exploratory data analysis to identify trends and insights that inform strategic actions.
Design and implement repeatable analytics pipelines, feature engineering strategies, and model validation frameworks.
Build advanced datasets and analytical assets using SQL, SAS, Python, or R in complex data environments.
Contribute to data modernization projects including cloud transitions and scalable data architecture improvements.
Communicate complex findings through compelling visual storytelling and presentations to enable rapid executive decision-making.
What we're looking for
Bachelor’s degree in an analytical, quantitative, or technical discipline.
5+ years of experience in business analytics and business support functions.
5+ years of experience with statistical/analytic languages including Python (Pandas, Scikit-Learn), Apache Spark, Hive, and Scala in a cloud environment.
5+ years of experience with database query and management tools such as SQL, Spark, Preseto, Athena, or Hive.
Hands-on experience with advanced analytics like logistic regression, time series, forecasting, optimization, and machine learning platforms.
Experience using GLMs, XGBoost, and other predictive analytic techniques.
Ability to translate business needs into technical requirements and influence decision makers.
Master’s degree in a quantitative field (preferred); experience with LTC insurance, ETL, big data ecosystems, or MLOps (preferred).
Python
R
SQL
pandas
NumPy
scikit‑learn
Tableau
Power BI
Matplotlib
Plotly
Machine Learning
Natural Language Processing
Copilot
ChatGPT
Gemini
Generative AI
Data Visualization
Data Mining
KPIs
Python
R
SQL
pandas
NumPy
scikit‑learn
Tableau
Power BI
Matplotlib
Plotly
Machine Learning
Natural Language Processing
Copilot
ChatGPT
Gemini
Data Visualization
Data Mining
KPIs