AI & Data Analytics Engineer

Overview

AI & Data Analytics Engineer

Key Responsibilities

• Automation & AI Development:

  Design, build, and maintain automated and AI-enhanced testing solutions to support audit activities, streamline manual processes, and increase data-driven insights.

• Coding, Scripting & AI Integration:

  Develop, document, and maintain scripts and tools (e.g., Python, SQL, R, or similar languages), incorporating machine learning and natural language processing (NLP) models for anomaly detection, predictive analytics, and intelligent audit sampling.

• Data Transformation, Analytics & AI Modeling:

  Extract, transform, and analyze large datasets using advanced analytics and AI techniques to identify anomalies, trends, and potential risk indicators.

• Testing Optimization:

  Partner with internal auditors to understand testing objectives and translate them into automated and intelligent approaches that improve efficiency, accuracy, and reliability.

• Tool & Process Innovation:

  Research and recommend emerging technologies, including AI, generative AI, and machine learning frameworks, that can be applied to audit testing and continuous monitoring.

• Collaboration:

  Work closely with Internal Audit team members and cross-functional stakeholders to ensure AI-enhanced solutions meet business requirements and align with audit objectives.

• Documentation & Training

  : Prepare clear documentation of automated and AI-driven testing processes and provide training/support to the audit team on the use of automation and AI tools.

Qualifications:

Experience and Skills:

• Bachelor’s Degree in data Analytics, Computer Science, Information Systems, Accounting Information Systems, or a related field.
• 10 Years+ hands-on coding experience with languages such as Python, R, SQL, or similar.
• Familiarity with AI frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and experience integrating

  machine learning models

  into business workflows.
• Understanding of

  AI ethics

  , model validation, and bias detection.
• Experience with data manipulation, automation frameworks, and analytics tools.
• Strong understanding of data integrity, data quality, and transformation processes.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong written and verbal communication skills to explain technical concepts to non-technical stakeholders.

Desirable Skills:

• Experience in internal audit, risk management, or compliance functions.
• Experience using

  generative AI tools

  (e.g., ChatGPT, GitHub Copilot) for process documentation, analysis, and code generation.
• Familiarity with audit testing methodologies or audit management software.
• Familiarity with audit testing methodologies or

  AI-assisted audit analytics

  .
• Experience with data visualization tools (Power BI, Tableau, Qlik, etc.).
• Exposure to ETL tools, APIs, or cloud-based data platforms.
• Knowledge of

  process mining

  , continuous auditing, and AI-based risk detection.

Soft Skills:

• Effective collaboration and communication skills, with a proven ability to work with interdisciplinary teams.
• Strategic thinker with a proactive approach to fraud risk assessment and process optimization.
• Commitment to upholding data integrity, confidentiality, and ethical standards in all forensic and data-driven activities.

Travel:

• Between 25%-50% travel is required

Amphenol Corporation is an equal opportunity employer and we encourage applications from all qualified candidates.