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AI/Data Automation Specialist

Job Summary:

The AI/Data Automation Specialist within the EY SAP Enterprise Data Management Initiative run by SAP Platforms & Assets will play a strategic and hands-on role in designing, implementing, and operationalizing intelligent automation and AI-powered capabilities that enhance EY’s SAP BDC data migration initiative. This role is crucial in enabling automation across data ingestion, transformation, validation, reconciliation, and governance using modern cloud-native technologies (SAP, Databricks, Snowflake, Microsoft, NVIDIA) integrated with SAP systems.

The ideal candidate combines advanced data science expertise, deep familiarity with cloud-based AI/ML services, and hands-on automation delivery experience to scale data quality and decision intelligence in complex SAP transformation programs.

Essential Functions of the Job:

• Lead design and development of AI/ML models for data profiling, anomaly detection, automated classification, NLP-based rule parsing, and predictive analytics on SAP and cloud-sourced datasets.
• Automate rule-based and intelligent data cleansing, matching, and enrichment activities across master and transactional data domains.
• Develop cognitive agents or bots for intelligent data extraction from unstructured and semi-structured sources (e.g., PDFs, scanned documents, Excel forms).
• Collaborate with SAP BDC engineers, MDM specialists, and data platform teams to embed intelligent automation into end-to-end data migration pipelines.
• Integrate AI/ML pipelines using cloud-native services (Azure ML, AWS SageMaker, Vertex AI, Nvidia AI) with ETL/ELT orchestration workflows (Databricks, ADF, Glue, or Airflow).
• Continuously monitor, retrain, and enhance deployed ML models using MLOps best practices.
• Assist with data labeling, synthetic data generation, and transfer learning for complex data scenarios.
• Document solution designs, maintain model explainability artifacts, and ensure AI solutions are auditable and ethically aligned.
• Evangelize the use of AI/automation across the BDC data lifecycle and provide mentoring to other team members.

Knowledge and Skills Requirements:

• Strong programming and modeling skills using Python, PySpark, R, SQL, and relevant ML libraries (scikit-learn, TensorFlow, XGBoost, Transformers).
• Experience building and operationalizing AI/ML models in cloud environments (SAP, Databricks, Microsoft).
• Expertise in data wrangling, feature engineering, and large-scale data processing frameworks (Spark, Pandas, Dask).
• Working knowledge of OCR/NLP techniques, including use of Tesseract, Azure Form Recognizer, or Amazon Textract.
• Proficiency in developing reusable automation scripts and agents using APIs, Python automation frameworks, or RPA platforms (e.g., Power Automate, UiPath).
• Familiarity with SAP master data and transactional structures to support intelligent mapping and transformation.
• Knowledge of MLOps tools and platforms (MLflow, Kubeflow, Seldon, Azure ML pipelines).
• Understanding of model bias, fairness, and ethical AI considerations.
• Excellent communication and stakeholder management skills; ability to translate AI outcomes into business language.

Other Requirements:

• Experience working in Agile data teams and across hybrid cloud/on-premise architectures.
• Strong documentation discipline and ability to communicate technical results to non-technical audiences.
• Experience in integrating AI automation into SAP data migration, BDC tools, or MDM pipelines is a strong advantage.
• Ability to drive innovation and continuously evaluate emerging AI technologies for applicability in enterprise data transformation.

Job Requirements:

Education:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field. A PhD is a plus.

Certifications (preferred):

• SAP AI / BDC / BTP certifications
• Databricks Certified ML Professional
• Microsoft Azure AI Engineer Associate

Experience:

• Minimum 6–10 years in data science, automation, or AI/ML engineering roles, with at least 2–3 years working on enterprise data platforms or SAP data transformations.

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