A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
What you’ll do: As a Data Scientist – Artificial Intelligence, your responsibilities include:
AI & Machine Learning Model Development
• Developing ML models for predictive analytics, fraud detection, and automation.
• Working with deep learning (DL) and Natural Language Processing (NLP) models for text and speech processing.
• Implementing AI-driven anomaly detection for data quality and governance.
Big Data & Model Deployment
• Building and deploying ML models on Cloudera Machine Learning (CML).
• Utilizing Apache Spark and PySpark for processing large-scale datasets.
• Working with Kafka and Iceberg to integrate AI solutions into real-time data pipelines.
Data Quality & Governance
• Supporting AI-powered data quality monitoring with Talend DQ.
• Assisting in metadata management, data lineage tracking, and automated data validation.
• Utilizing Denodo for AI-driven data virtualization and federated learning.
Security & Compliance
• Ensuring AI models comply with Bank’s data security and governance policies.
• Supporting AI-driven encryption and anomaly detection techniques using Thales CipherTrust.
Collaboration & Documentation
• Working with data engineers and analysts to develop AI solutions aligned with business needs.
• Documenting model architectures, experiment results, and optimization techniques.
• Assisting in AI-driven reporting and visualization using Qlik Sense/Tableau.
4-7 years of experience in AI, ML, and Data Science.
• Strong programming skills in Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with big data platforms (Cloudera, Apache Spark, Kafka, Iceberg).
• Experience with NLP, deep learning, and AI for automation.
• Understanding of data governance, metadata management, and AI-driven data quality.
• Familiarity with GitLab, Sonatype Nexus, and CheckMarx for AI model deployment.
Experience with AI/ML solutions for Banking and financial services.
• Knowledge of cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
• Exposure to AI ethics, explainable AI (XAI), and bias detection in ML models.
• Understanding of graph databases (DGraph Enterprise) for AI-powered insights.
• Certifications in IBM AI Engineering, Cloudera Data Science, or Google/AWS AI.