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