✦ Luna Orbit — Data & Analytics

Data Scientist

at Intercontinental Exchange

Unknown Posted March 18, 2026
Type Not Specified
Experience mid
Exp. Years 3+ years
Education Bachelor's or Master's in Computer Science, Statistics, Mathematics, Data Science, or related field
Category Data & Analytics

This role involves analyzing loan data to identify trends, develop models, and generate insights to support financial decision-making and risk management.

  • Analyze loan data
  • Develop data models
  • Generate insights
  • Collaborate with stakeholders
  • Build data pipelines

Proficiency in Python, R, SQL, machine learning, and data visualization tools like Tableau and Power BI, with experience in loan data analysis and data pipeline development.

The ideal candidate is a data scientist with 3+ years of experience in loan data analysis, proficient in Python, R, and SQL, with strong skills in machine learning and data visualization, capable of translating complex data into actionable insights.

3+ years relevant experienceProficiency in PythonRSQLExperience with loan data analysisData visualization skillsKnowledge of machine learning techniques
Master's or Ph.D. in related fieldExperience with SigmaExperience in financial markets
PythonRSQLpandasNumPyscikit-learnTableauPower BI
PythonRSQLdata analysismachine learningdata visualizationpandasNumPyscikit-learnTableauPower BI
PythonRSQLData AnalysisMachine LearningData VisualizationPandasNumPyscikit-learnTableauPower BI
Analytical thinkingProblem-solvingCommunicationCollaborationStakeholder engagementData storytelling
Industry Financial Services / Fintech
Job Function Perform data analysis and modeling to support loan market strategies
Role Subtype Data Analyst
Tech Domains Python, R, SQL, Data Analysis, Machine Learning, Data Visualization
data scientistloan data analysismachine learningdata visualizationPythonRSQLdata analysisstatisticsfinancial datadata pipelinesdata modelingstakeholder communicationdata storytellinganalyticsdata engineering

Less than 3 years relevant experience, Lack of proficiency in Python, R, or SQL, No experience with loan data or financial data, Poor communication skills

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