Data Scientist - Financial Services (Abu Dhabi)

About the role

Accelerone is hiring a Data Scientist for its AI & Data Center of Excellence in Abu Dhabi, UAE. The role designs and delivers advanced analytical and machine learning solutions that support core financial decisions in lending, risk, collections and customer engagement. It calls for statistical rigor, business acumen and production-oriented thinking, with a focus on financial services use cases.

Two experience bands are offered: Senior Data Scientist (8-10 years) and Mid-Level Data Scientist (5-7 years).

Key responsibilities

• Develop and deploy machine learning models for credit risk scoring, fraud detection, customer segmentation and CLV, and collections optimization
• Turn complex business problems into analytical frameworks and measurable outcomes
• Perform exploratory data analysis on structured and unstructured data such as transactions, call logs, financial records and documents
• Design scalable ML pipelines with Data and AI Engineering teams
• Lead model validation, explainability and regulatory compliance (e.g. IFRS9, Basel guidelines)
• Build reusable data science components, models and accelerators
• Present insights, recommendations and model performance to senior stakeholders

Required profile

• Hands-on experience in at least one financial use case: credit underwriting (retail, MSME, microfinance), fraud detection and AML analytics, early warning systems, collections prioritization, or customer 360 analytics
• Experience managing the full model lifecycle and demonstrating business impact (revenue, risk, efficiency)
• Previous experience in banks, NBFCs or microfinance organizations is preferred
• Strong communication skills and ability to work in cross-country or distributed teams

Required skills

• Python (mandatory); R or Scala optional
• Scikit-learn, TensorFlow, PyTorch, XGBoost
• Deep learning, NLP, time series modeling, graph analytics
• SQL, Spark, Hive, big data ecosystems
• AWS, Azure, GCP
• Exposure to large language models and applied AI is preferred