JOBS by allUP
Join to apply for the
Senior Data Analyst
role at
JOBS by allUP Get AI-powered advice on this job and more exclusive features. This range is provided by JOBS by allUP. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range
$70,000.00/yr - $110,000.00/yr About our client
Worth AI , a forward-thinking company in the computer software industry, is looking for a detail-oriented and analytical individual to join its team as a Senior Data Analyst. At Worth AI, the company strives to drive impactful decision-making through insights derived from data, while upholding values of one team, extreme ownership, and creating raving fans both internally and for customers. About the role
As a
Senior Data Analyst
within Worth AI’s fintech organization, the selected candidate will play a critical role in analyzing and optimizing the data that drives credit decisioning, underwriting, and fraud prevention models. This individual will work closely with Finance, Risk, Product, and Engineering teams to mine large and complex datasets, build dashboards, write business-critical queries, and help steer the company’s AI-driven underwriting strategy. The role requires both business acumen and technical proficiency, including a solid understanding of data engineering principles and the ability to deliver scalable analytics solutions in a regulated environment.
Responsibilities
Mine and analyze large-scale credit, transactional, and behavioral datasets to identify trends, anomalies, and insights that inform credit risk, underwriting, fraud, and pricing strategies.
Write performant SQL queries to extract, transform, and analyze data across structured and semi-structured sources (including loan-level, customer, and bureau data).
Design, build, and maintain interactive dashboards and reporting tools to support Finance, Risk, Credit, and Executive teams in monitoring key performance indicators.
Partner with Data, Finance, Product, and Engineering teams to define and track key metrics for credit performance, loss forecasting, and portfolio health.
Support the development and ongoing evaluation of AI/ML models by providing exploratory data analysis, historical performance context, and business rule validation.
Collaborate with data engineering and data science teams to ensure pipelines are reliable, secure, and meet both operational and regulatory standards.
Automate recurring reports and analyses to improve visibility and reduce manual workflows across the credit and finance lifecycle.
Contribute to model governance efforts by ensuring documentation, auditability, and transparency of data inputs used in risk models and decision engines.
Stay informed on regulatory and compliance requirements related to data usage in financial services (e.g., Fair Lending, ECOA, GLBA) and align analytics practices accordingly.
Qualifications
Bachelor's degree in Data Science, Statistics, Finance, Computer Science, or a related technical field
4+ years of experience in a data analytics or business intelligence role, ideally in a fintech, financial services, or credit risk environment
Advanced SQL skills and experience working with cloud data platforms (e.g., AWS Redshift, Athena, Snowflake, BigQuery)
Strong experience with data visualization tools like Tableau, Power BI, or Looker, and the ability to build intuitive dashboards for business stakeholders
Solid understanding of credit risk concepts, underwriting processes, and key lending KPIs such as delinquency, charge-off rates, loss curves, and approval funnels
Exposure to AI/ML-based decision systems, especially in underwriting, fraud detection, or credit scoring contexts
Working knowledge of data engineering fundamentals and modern data stack tools (e.g., dbt, Airflow, ETL pipelines)
Proficiency in Excel for detailed analysis and cross-functional reporting
Bonus: Experience with Python or other scripting languages for data analysis and automation
Excellent communication and problem-solving skills, with the ability to present complex data insights to technical and non-technical stakeholders alike
High standards for data integrity, governance, and regulatory compliance in a financial environment
Benefits
Life Insurance
Unlimited Paid Time Off
9 paid Holidays
Family Leave
Work From Home
Free Food & Snacks (Access to Industrious Co-working Membership!)
Wellness Resources
#J-18808-Ljbffr
Senior Data Analyst
role at
JOBS by allUP Get AI-powered advice on this job and more exclusive features. This range is provided by JOBS by allUP. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range
$70,000.00/yr - $110,000.00/yr About our client
Worth AI , a forward-thinking company in the computer software industry, is looking for a detail-oriented and analytical individual to join its team as a Senior Data Analyst. At Worth AI, the company strives to drive impactful decision-making through insights derived from data, while upholding values of one team, extreme ownership, and creating raving fans both internally and for customers. About the role
As a
Senior Data Analyst
within Worth AI’s fintech organization, the selected candidate will play a critical role in analyzing and optimizing the data that drives credit decisioning, underwriting, and fraud prevention models. This individual will work closely with Finance, Risk, Product, and Engineering teams to mine large and complex datasets, build dashboards, write business-critical queries, and help steer the company’s AI-driven underwriting strategy. The role requires both business acumen and technical proficiency, including a solid understanding of data engineering principles and the ability to deliver scalable analytics solutions in a regulated environment.
Responsibilities
Mine and analyze large-scale credit, transactional, and behavioral datasets to identify trends, anomalies, and insights that inform credit risk, underwriting, fraud, and pricing strategies.
Write performant SQL queries to extract, transform, and analyze data across structured and semi-structured sources (including loan-level, customer, and bureau data).
Design, build, and maintain interactive dashboards and reporting tools to support Finance, Risk, Credit, and Executive teams in monitoring key performance indicators.
Partner with Data, Finance, Product, and Engineering teams to define and track key metrics for credit performance, loss forecasting, and portfolio health.
Support the development and ongoing evaluation of AI/ML models by providing exploratory data analysis, historical performance context, and business rule validation.
Collaborate with data engineering and data science teams to ensure pipelines are reliable, secure, and meet both operational and regulatory standards.
Automate recurring reports and analyses to improve visibility and reduce manual workflows across the credit and finance lifecycle.
Contribute to model governance efforts by ensuring documentation, auditability, and transparency of data inputs used in risk models and decision engines.
Stay informed on regulatory and compliance requirements related to data usage in financial services (e.g., Fair Lending, ECOA, GLBA) and align analytics practices accordingly.
Qualifications
Bachelor's degree in Data Science, Statistics, Finance, Computer Science, or a related technical field
4+ years of experience in a data analytics or business intelligence role, ideally in a fintech, financial services, or credit risk environment
Advanced SQL skills and experience working with cloud data platforms (e.g., AWS Redshift, Athena, Snowflake, BigQuery)
Strong experience with data visualization tools like Tableau, Power BI, or Looker, and the ability to build intuitive dashboards for business stakeholders
Solid understanding of credit risk concepts, underwriting processes, and key lending KPIs such as delinquency, charge-off rates, loss curves, and approval funnels
Exposure to AI/ML-based decision systems, especially in underwriting, fraud detection, or credit scoring contexts
Working knowledge of data engineering fundamentals and modern data stack tools (e.g., dbt, Airflow, ETL pipelines)
Proficiency in Excel for detailed analysis and cross-functional reporting
Bonus: Experience with Python or other scripting languages for data analysis and automation
Excellent communication and problem-solving skills, with the ability to present complex data insights to technical and non-technical stakeholders alike
High standards for data integrity, governance, and regulatory compliance in a financial environment
Benefits
Life Insurance
Unlimited Paid Time Off
9 paid Holidays
Family Leave
Work From Home
Free Food & Snacks (Access to Industrious Co-working Membership!)
Wellness Resources
#J-18808-Ljbffr