What you'll do
- Build ML models for banking use cases like credit scoring, fraud detection, and customer segmentation
- Develop deep learning and GenAI components using transformers, embeddings, and fine-tuning
- Create scalable data and feature pipelines for experimentation, model training, and deployment
- Implement model evaluation frameworks covering accuracy, robustness, explainability, bias, drift, and business value
- Develop MLOps workflows for reproducible, observable, governed, and continuously improvable models
- Integrate ML capabilities into banking products, workflows, and platforms through APIs and services
- Conduct A/B testing and performance benchmarking to validate solution quality and impact
- Develop reusable ML assets, patterns, and best practices across AI Hub squads
Key requirements
- 2+ years' experience
- Strong Python skills with libraries like NumPy, Pandas, scikit-learn, PyTorch, TensorFlow, or Keras
- Experience in ML model development including supervised and unsupervised learning, deep learning, NLP, feature engineering, and predictive modeling
- Knowledge of GenAI and LLM techniques including transformers, embeddings, fine-tuning, and task-specific adaptation
- Expertise in scalable data pipelines and MLOps for training, evaluation, deployment, monitoring, and improvement
- Familiarity with Azure ML, Azure AI Services, Databricks, Spark, SQL, and NoSQL databases
- Skills in model evaluation and benchmarking including accuracy, robustness, explainability, bias, drift, and Responsible AI governance
- Computer Science / Engineering / Mathematics / Statistics / Data Sciencepreferred
Benefits
- Competitive salary and benefits including life/health insurance, performance bonuses, flexible work, employee share purchase plan, parental leave, continuous training and development, career coaching, diverse and inclusive culture, and corporate citizenship initiatives.
About the job
ARE YOU READY to step into the New Era (NewRA) of AI-driven banking?
At Accenture Newra AI Hub, we are not just building technology, we are redefining how banking operates. As part of our strategic collaboration with Piraeus, Newra is designed to responsibly embed AI at the core of its business, moving beyond experimentation to real-world impact at scale. Built to make a real difference, Newra reflects our belief that AI creates value only when it genuinely improves people’s lives.
You will work on advanced AI solutions that span the full spectrum of the bank -from core banking systems to customer experience- simplifying complexity, automating critical processes and delivering measurable results where they matter most.
Joining Newra means becoming part of a high-performing team of innovators at the beginning of a major reinvention. This is a space for people who approach AI with depth, discipline and purpose. You will collaborate across disciplines, develop future-proof skills, and help turn technology into real-world transformation.
As an AI/ML Scientist, you’ll build practical, scalable AI and ML solutions for a leading bank, from credit risk and fraud detection to customer intelligence, automation, and GenAI-enabled services. You'll work across the full ML lifecycle: data pipelines, model training, evaluation, and production deployment using MLOps best practices, collaborating closely with engineers, product teams, and banking experts, to turn research into measurable impact.
What you'll build
ML models for banking use cases: credit scoring, fraud detection, customer segmentation, personalisation, risk intelligence, and process automation
Deep learning and GenAI components using transformers, embeddings, fine-tuning, and task-specific model adaptation
Scalable data and feature pipelines that support experimentation, model training, validation, and production deployment
Model evaluation frameworks covering accuracy, robustness, explainability, bias, drift, and business value
MLOps workflows that make models reproducible, observable, governed, and continuously improvable
APIs, services, and model integrations that embed ML capabilities into banking products, workflows, and internal platforms
A/B testing and performance benchmarking approaches to validate solution quality and measurable impact
Reusable ML assets, patterns, and best practices shared across AI Hub squads
Qualification
What we need
B.Sc., M.Sc. or PhD in Computer Science, Engineering, Mathematics, Statistics, Data Science, or equivalent experience
Strong Python with NumPy, Pandas, scikit-learn, PyTorch, TensorFlow, or Keras
2–3 years developing, validating, and improving ML models for real-world use cases
Solid grasp of supervised / unsupervised learning, deep learning, NLP, feature engineering, and predictive modelling
Hands-on with GenAI and LLM techniques: transformers, embeddings, fine-tuning, prompt experimentation, model adaptation
Experience with scalable data pipelines and MLOps for training, evaluation, deployment, monitoring, and improvement
Familiarity with Azure ML, Azure AI Services, Databricks, Spark, SQL, or NoSQL databases
Understanding of model evaluation, benchmarking, explainability, bias, drift, Responsible AI, and governance
Nice to have:
MLOps tooling: MLflow, Kubeflow, Airflow; cloud AI platforms, Databricks / Spark
GPU systems familiarity for training optimisation
Responsible AI: model benchmarking, A/B testing, governance and audit requirements
What's in it for you
Competitive salary and benefits, including but not limited to: life/health insurance, performance based bonuses, monthly vouchers, company car (depending on management level), flexible work arrangements, employee share purchase plan, parental leave and various corporate discounts
Continuous training & development through global platforms & local academy. At Accenture, we believe in bringing the best to our clients through continuous learning & improvement – from basic skills to industry-specific content – available to all our people
Career coaching and mentorship to help you manage your career and develop professionally
Ongoing strength and skill-based evaluation process
Various opportunities to develop your career across a spectrum of clients, industries and projects
Diverse and inclusive culture
Opportunities to get involved in corporate citizenship initiatives, from volunteering to doing charity work
Under our Brain Regain initiative, extra relocation benefits may apply




