Data Scientist

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