Lead, Data Science Internal Audit

AbbVie

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Plainfield, NJ
Salary
$96,500–$183,500 / yr
Posted
31 days ago
Freshness
Confirmed live yesterday
Closes
Aug 11, 2126

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $182k
This role $140k
$81k most similar roles pay here $240k

This role pays less than 81% of similar roles. Most pay $152,875–$211,200 — the shaded band above. At the midpoint, this role pays about $140k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

About AbbVie

AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.

AbbVie currently has 297 open roles on FindRole.

Listed pay typically runs $109,500–$208,500 across 271 roles with salary data.

Most-posted roles

View all roles at AbbVie

At a glance

TL;DR · Lead, Data Science Internal Audit

The Lead, Data Science Internal Audit joins the Data Analytics, Internal Audit team to enhance audit impact by leveraging data-driven insights to identify risks and operational improvements. This role involves designing advanced statistical models, including decision trees, regression analyses, and natural language processing (NLP) techniques to detect anomalies and risk indicators across enterprise datasets. The individual will develop population-level analytics frameworks, build predictive models for risk profiling, and create automated data pipelines and monitoring dashboards for real-time detection of control failures. Key responsibilities include translating audit objectives into analytical approaches, mentoring junior team members, and presenting complex findings to leadership. The role requires proficiency in Python, SQL, R, and PowerBI or Tableau. This position addresses the business problem of proactively identifying compliance issues and fraudulent activities within large, unstructured data sources like contracts and transaction narratives.

What you'll do

  • Design and implement advanced statistical models including decision trees, regression analyses, and NLP to identify risk indicators.
  • Develop and maintain population-level data analytics frameworks for ad-hoc testing and continuous monitoring.
  • Build predictive models and classification algorithms to assess risk profiles and prioritize audit focus areas.
  • Apply NLP techniques to analyze unstructured data sources like contracts and emails to detect fraud or compliance issues.
  • Create automated data pipelines and monitoring dashboards to enable real-time detection of control failures.
  • Define key risk indicators and develop statistical thresholds for continuous monitoring alerts.
  • Mentor junior team members on data science techniques, statistical best practices, and audit analytics applications.
  • Present complex analytical findings to leadership in clear, actionable formats to support audit conclusions.

What we're looking for

  • Bachelor’s degree in Computer Science, Statistics, Data Science, or a related field.
  • Master's degree or MBA in a relevant field is preferred.
  • Minimum of 6 years of progressive and related experience.
  • Proficiency in Python, SQL, and R.
  • Experience with PowerBI or Tableau is preferred.
  • Ability to design advanced statistical models including decision trees, regression analyses, and NLP techniques.
  • Ability to build predictive models, automated data pipelines, and monitoring dashboards.
  • Ability to mentor junior team members on data science techniques and audit analytics.

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