About the company
We are Qatar Insurance Company (QIC), the leading insurance provider in GCC. With a history dating back to 1964, we have established ourselves as a pioneer in the insurance industry, offering innovative solutions to meet the diverse needs of individuals and businesses.
Our vision is to make QIC group become the first Digital Ecosystem in the region by combining insurance and non-insurance services in one platform. Through our digital platforms, such as qic.online and the QIC app, we empower customers to manage their needs anytime and anywhere.
Our employees have been featured in Forbes 30 under 30, teach at online universities, serve on program committees of major IT conferences, and have previously worked at Yandex, Tinkoff, Avito, Ozon, and other leading tech companies.
About the position
As a Senior Data Scientist, you will be at the forefront of our ML journey – building powerful, scalable models that target fraud, reduce losses, and drive revenue through smart recommendation systems. Your work directly influences key business outcomes and paves the way for our evolving AI capabilities.
Responsibilities
Research and Model Development
- Analyze business tasks and formulate ML problem statements together with product teams
- Exploratory Data Analysis: exploring insurance data, identifying patterns and insights
- Feature Engineering: creating features from raw data (transactions, policies, claims, behavioral data)
- Model Prototyping: rapid validation of hypotheses and MVP solutions
- A/B Testing: designing experiments to validate ML solutions
Production Development
- Model deployment to production: from Jupyter notebook to production API
- ML pipeline setup: automation of training, validation, and deployment
- Real-time inference: integrating models into business processes (underwriting, claims processing)
- Model monitoring: tracking performance, drift detection, alert systems
- Performance optimization: accelerating inference, scaling workloads
Requirements
Technical Skills
- Background with financial/insurance data is an advantage
- 5+ years of experience in ML/DS with a focus on product development
- Programming languages: Python (advanced level), SQL
- ML stack: scikit-learn, XGBoost, LightGBM, CatBoost, pandas, numpy
- Deep Learning: TensorFlow or PyTorch for NLP and recommendation systems
- MLOps: experience deploying models into production (Docker, CI/CD, monitoring)
- Big Data: PySpark or similar tools for large-scale datasets
- Git and collaborative development
Professional Competencies
- Feature Engineering: creating and selecting features for various types of data
- Model Validation: cross-validation, A/B testing, quality metrics
- Statistics: probability theory, hypothesis testing, confidence intervals
- Working with imbalanced data (critical for anti-fraud tasks)
- Time Series Analysis: forecasting and trend analysis
- Model interpretability: SHAP, LIME to explain results to business stakeholders
