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Data Scientist- Knowledge Graph

MphasiS Corporation USABerkeley Heights, NJ🇺🇸United StatesPosted Sep 26, 2026

Why This Role Stands Out

This role offers a fantastic opportunity to leverage your expertise in regression analysis and knowledge graphs to drive significant impact within a reputable company. You'll thrive here if you possess strong analytical skills and enjoy dissecting complex data to uncover insights and solve problems. Apply to contribute to impactful data-driven solutions.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Berkeley Heights, NJ, United States
Posted
2 weeks ago
SQLMachine LearningSnowflakeTableauHadoopPower BIPython

Job Description

Data Scientist (Regression Analysis & Knowledge Graphs) 

Location: Berkeley Heights, NJ (5days Onsite)

Contract

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.
  • Faster remediation and resolution of issues.

Ideal Candidate: A data scientist who can use regression analysis, statistical modeling, and data visualization to detect drift, explain variances, identify root causes, and help teams resolve defects faster.

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