Role description
Data Scientist - Regression Analysis
Role Summary
Analyze data to identify trends, detect variances, explain root causes, and support defect remediation
using statistical and regression analysis.
Key Responsibilities
• Build and validate regression models to explain data drift and variances.
• Analyze mismatches between expected and actual results.
• Identify root causes of defects and data quality issues.
• Perform statistical testing and trend analysis.
• Create dashboards, heat maps, and visualizations to monitor drift.
• Develop predictive models to detect issues early.
• Partner with business, QA, and development teams to prioritize fixes.
• Present findings and recommendations to stakeholders.
Required Skills
• Strong knowledge of regression analysis and statistics.
• Experience with Python, SQL, Big Data, Hadoop, and data visualization tools. Machine
learning experience is a plus.
• Ability to analyze large datasets and identify patterns.
• Experience with root cause analysis and anomaly detection.
• Strong communication and problem - solving skills.
Preferred Experience
• Financial services or payments experience.
• Data reconciliation and validation.
• Drift monitoring and predictive analytics.
• Power BI, Tableau, Spark, Snowflake, or Databric
Success Measures
• Faster defect diagnosis.
• Earlier detection of drift.
• Improved validation accuracy.
• Reduced manual analysis effort.
Ideal Candidate:
A data scientist who can use regression analysis, statistical modeling, and data visualization to detect
