AI/ML Scientist for Newra, Part of Accenture
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AI/ML Scientist for Newra, Part of Accenture
Location
Athens, Central Athens, Greece
Experience
Mid
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantFull-timeWork from Office
Job Description
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
**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
To learn more about Accenture, and how you will be challenged and inspired from Day 1, please visit our website accenture.com/gr-en/.
Key Responsibilities
- Build ML models for banking use cases including credit scoring, fraud detection, and customer segmentation
- Develop deep learning and GenAI components using transformers and embeddings
- Create scalable data and feature pipelines for model training and production deployment
- Implement model evaluation frameworks covering accuracy, robustness, and explainability
- Establish MLOps workflows for reproducible and governed model management
- Develop APIs and services to embed ML capabilities into banking products
- Conduct A/B testing and performance benchmarking to validate solution quality
Requirements
- B.Sc.
- M.Sc. or PhD in Computer Science
- Engineering
- Mathematics
- Statistics
- Data Science
- or equivalent experience
Skills Required
PythonNumPyPandasscikit-learnPyTorchTensorFlowKerasSupervised learningUnsupervised learningDeep learningNLPFeature engineeringPredictive modellingGenAILLM techniquesTransformersEmbeddingsFine-tuningPrompt experimentationModel adaptationData pipelinesMLOpsAzure MLAzure AI ServicesDatabricksSparkSQLNoSQL databasesModel evaluationBenchmarkingExplainabilityBiasDriftResponsible AIGovernanceCollaborationProblem solvingAttention to detailMLflowKubeflowAirflowCloud AI platformsGPU systems
Benefits
- Competitive salary
- Life/health insurance
- Performance based bonuses
- Monthly vouchers
- Company car
- Flexible work arrangements
- Employee share purchase plan
- Parental leave
- Corporate discounts
- Continuous training & development
- Career coaching and mentorship
- Diverse and inclusive culture
- Corporate citizenship initiatives
- Relocation benefits
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