Role Summary
We are seeking a Data Scientist with strong expertise in regression analysis and statistical modeling to analyze data trends, detect variances, explain root causes, and support defect remediation. The ideal candidate will have hands‑on experience with large datasets, anomaly detection, and predictive analytics, working closely with QA, business, and development teams.
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
Hands‑on with Python, SQL, Big Data, Hadoop
Experience with data visualization tools (Power BI, Tableau, etc.)
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 domain
Data reconciliation and validation
Drift monitoring and predictive analytics
Tools: Power BI, Tableau, Spark, Snowflake, Databricks
Success Measures
Faster defect diagnosis
Earlier detection of drift
Improved validation accuracy
Reduced manual analysis effort
Faster remediation and resolution of issues
Ideal Candidate
A data scientist who can leverage regression analysis, statistical modeling, and visualization to detect drift, explain variances, identify root causes, and help teams resolve defects faster.