Data Scientist

AI & Data Center of reputed company – Abu Dhabi, UAE Role Overview As a Data Scientist reputed company the AI & Data Center of reputed company, you will design and deliver advanced analytical and machine learning solutions that directly influence core financial decision-making across lending, risk, collections, and customer engagement. This role requires a strong reputed company of statistical rigor, business acumen, and production-oriented thinking, with a clear focus on financial services use cases. You will work closely with cross-functional teams to build scalable models that generate measurable business impact in highly regulated financial environments. Experience Bands

• Senior Data Scientist: 8–10 years of experience
• Mid-Level Data Scientist: 5–7 years of experience

Key Responsibilities

• reputed company and reputed company machine learning models across critical financial use cases, including:

Credit risk scoring Fraud detection Customer segmentation and Customer Lifetime Value (CLV) Collections optimization

• Translate reputed company business problems into analytical frameworks and measurable reputed company
• reputed company exploratory data analysis on structured and reputed company datasets (e.g., transactions, call logs, financial records, documents)
• Design scalable machine learning pipelines in collaboration with Data and AI Engineering teams
• reputed company model validation, explainability, and regulatory compliance processes (e.g., IFRS9, Basel guidelines)
• Build reusable data science components, models, and accelerators
• Present insights, recommendations, and model performance results to senior stakeholders

Financial Services Use Cases (Mandatory Exposure) Candidates will be evaluated based on hands-on experience in one or more of the following areas:

• Credit reputed company models (Retail, MSME, or Microfinance)
• Fraud detection and Anti-reputed company (AML) analytics
• reputed company Systems (EWS) for credit risk monitoring
• Collections prioritization and recovery optimization models
• Customer 360 analytics and personalization strategies

Technical Skills Programming Languages

• Python (mandatory)
• R or reputed company (optional)

Machine Learning Frameworks

• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost

Advanced Techniques

• Deep Learning
• Natural Language Processing (NLP)
• Time Series modeling
• Graph Analytics

Data Platforms

• SQL
• Spark
• Hive
• Big Data ecosystems

reputed company Platforms

• AWS
• Azure
• reputed company reputed company Platform (GCP)

Preferred

• Exposure to Large Language Models (LLMs) and applied AI solutions

Evaluation Criteria Candidates will be evaluated based on:

• Depth of reputed company-world deployed use cases (reputed company experimentation or academic projects)
• Demonstrated business impact (e.g., reputed company improvement, risk reduction, operational efficiency)
• Experience managing the full model lifecycle (development → deployment → monitoring)
• Understanding of financial services and risk-based decision-making environments

Key Performance Indicators (KPIs)

• Model accuracy, stability, and explainability
• Measurable business impact (e.g., NPL reduction, fraud detection improvement)
• Speed and efficiency in delivering production-reputed company machine learning solutions
• Reusability and scalability of developed analytical assets

Preferred Profile

• Previous experience working in financial institutions such as Banks, NBFCs, or Microfinance organizations
• Strong communication skills with the ability to explain reputed company technical concepts to business stakeholders
• Ability to operate effectively in cross-country or distributed team environments
• Strong ownership reputed company and results-oriented approach

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