Data Scientist I

Pathward

. Analyze large and complex datasets using statistical, predictive, and other analytical techniques to generate actionable business insights .

Posted 11/10/2026full-timeRemote • United StatesJuniorMid-Level💰 $57,582 - $106,345 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data analysis, predictive modeling, and statistical techniques to derive actionable insights from large datasets. Proficient in Python and SQL for data validation and automation, with strong communication skills for technical documentation and stakeholder collaboration.

Highest-signal resume keywords

Python ProgrammingSQL Data AnalysisPredictive ModelingData Quality ValidationTechnical Documentation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical AnalysisData ProfilingRoot-Cause AnalysisAutomation ProcessesAnalytical Techniques

Soft Skills

Problem-SolvingAttention to DetailCollaborationCuriosityCommunication

Tools & Technologies

SnowflakeAWSPower BIGenerative AI ToolsGit

Industry Keywords

BankingFinancial ServicesFintechConsumer CreditModel Governance

Tech Stack

Tools & technologies

AWSPythonSnowflakeSQL

About the role

Key responsibilities & impact

Analyze large and complex datasets using statistical, predictive, and other analytical techniques to generate actionable business insights
Support development, testing, implementation, and monitoring of predictive models and analytical solutions
Support partner model and program onboarding, oversight, and ongoing monitoring, including data validation, performance analysis, documentation, and issue resolution
Perform data quality analysis with business context, identifying root causes, downstream impacts, and opportunities to improve data reliability and usability
Develop and maintain monitoring processes for models, partner portfolios, products, and critical data
Create comprehensive technical documentation covering data, methodologies, business requirements, testing, model performance, monitoring, assumptions, and limitations
Use approved AI-assisted tools to improve documentation, coding, analysis, quality assurance, and workflow efficiency while independently validating outputs
Collaborate with business, risk, compliance, technology, operations, vendors, and external partners to implement and maintain analytical solutions
Develop reusable and automated processes to improve monitoring, reporting, data validation, and Data Science workflows
Communicate analytical findings, risks, and recommendations clearly to technical and nontechnical stakeholders

Requirements

What you’ll need

Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Engineering, Computer Science, Finance, Business Analytics, or a related quantitative field
Up to 2+ years of relevant professional, internship, research, or project experience
Experience working with large datasets and applying analytical or statistical methods to business problems
Hands-on experience with Python and SQL for data analysis, validation, and automation
Strong analytical and problem-solving skills with the ability to connect technical findings to business processes and outcomes
Experience with data profiling, reconciliation, root-cause analysis, and data quality validation
Strong written communication skills with the ability to produce detailed technical and analytical documentation
Ability to manage multiple analytical, monitoring, and documentation responsibilities with strong attention to detail
Curiosity and willingness to learn new business areas, analytical techniques, technologies, and AI-enabled tools
Strong collaboration skills and ability to work effectively with business and technical stakeholders
Experience or familiarity with Python, SQL, Snowflake, and AWS in an analytical or Data Science environment
Experience in banking, financial services, fintech, consumer credit, payments, fraud, or other regulated industries
Experience with partner onboarding, partner/model oversight, portfolio monitoring, or model governance
Familiarity with predictive modeling and model-performance measures such as AUC, KS, stability, approval rates, and portfolio performance
Experience with Power BI or similar visualization tools
Familiarity with Git/version control and reproducible development practices
Experience using generative AI tools for coding, analysis, research, or technical documentation with appropriate human review

Benefits

Comp & perks

Annual performance-based incentive opportunity
Health insurance
401(k) retirement benefits
Life insurance
Disability benefits
Paid time off
Comprehensive benefits package for eligible employees