aurangzaib1

Senior Data Scientist

Data-focused technologist with a track record of building reliable, automated, high-scale production systems and turning complex data into actionable operational insight. Eleven years of experience designing and operating data pipelines, anomaly detection, and alerting solutions that improve operational monitoring and incident visibility. Strong Python, SQL, AWS and CI/CD foundation paired with practical experience in log-heavy telemetry, Grafana monitoring, and automation. Process-oriented investigator comfortable following playbooks while exercising judgment during ambiguous triage, communicating findings to stakeholders, and collaborating with engineering to operationalize detection and response workflows. Ready to transition these skills into SOC L1 triage and incident response roles, leveraging SIEM log analysis, alert tuning, and orchestration platforms.

Experience

Jan 2019 — Present

Senior Data Scientist

ComScore

  • Maintained an Isolation Forest anomaly detection system in Python to identify anomalous traffic and potential fraud,
  • implemented automated alerting and investigative dashboards which enabled triage teams to reduce investigation
  • time by 20% while improving detection precision.
  • Managed end-to-end delivery of a Python and Snowflake data product with CI/CD workflows, producing
  • standardized telemetry views and playbook-aligned reports that enabled consistent incident review across 10+
  • teams and improved cross-team resolution consistency.
  • Operationalized an XGBoost-based risk scoring model into production to prioritize high-risk events, mapped scoring
  • outputs into ticketing priorities and helped shift resources to higher impact investigations, contributing to a 20%
  • improvement in resource allocation efficiency.
  • Built PySpark and SQL pipelines to process billions of web-log records daily, standardized event schemas for
  • downstream log analysis and SIEM ingestion, automated nightly validations and reduced data delivery lag to same-
  • day availability for triage and alerting.

Apr 2021 — Jul 2022

Data Scientist (Contract)

Cloudeagle.AI

  • Built and operate high-throughput log ingestion pipelines in Python on AWS to collect application and telemetry
  • events, implemented alerting to Grafana and automated health checks which reduced mean time to detect pipeline
  • failures by 45% while preserving 99.9% uptime for customer-facing services.
  • Designed anomaly detection models using TensorFlow and vector indexing to surface abnormal user and system
  • behaviors, integrated model output with SIEM-style alert consumers and reduced false positive alerts by 18%
  • through threshold tuning and feature selection.
  • Led design and deployment of Kafka-based real-time event streaming and Spark Streaming consumers to correlate
  • multi-source logs for faster triage, automated initial enrichment of alerts and improved incident correlation rates by
  • 32% for downstream analysts.
  • Collaborated with engineering to create CI/CD pipelines and playbook-driven runbooks for automated triage
  • workflows, integrating alert enrichment and ticket creation to ServiceNow, resulting in a 25% reduction in manual
  • investigation steps per incident.

Education

Jan 2020

WorldQuant University

Master of Science in Financial Engineering in Financial Engineering · Financial Engineering

Jan 2019 — Feb 2019

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Jan 2018

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Jan 2010 — Dec 2014

Whittier College

Bachelor of Arts in Mathematics in Mathematics · Mathematics

Jan 2006 — Dec 2010

Emory University

Bachelor of Science in Mathematics & Economics in Mathematics & Economics · Mathematics & Economics

Skills

  • Palo Alto XSOAR
  • Palo Alto XDR
  • Proofpoint
  • ServiceNow
  • SIEM
  • Log analysis
  • Incident response
  • IAM
  • Microsoft
  • Python
  • SQL
  • AWS
  • CI/CD
  • Grafana
  • XGBoost
  • PySpark
  • Snowflake
  • TensorFlow
  • Kafka
  • Spark Streaming