Data Scientist

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4 days ago

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Robusta Studio

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robusta is a tech agency working with a diverse client base across different sectors & industries on implementing digital transformation programs. Engagements are typically focused on digitization of existing operations & processes and/or activation of digital customer engagement channels. With a team of 100+ tech and market consultants, robusta maintains an impactful footprint across EMEA and engages with its clients through its two key operations hubs in Egypt and Germany.

51 - 200 employees

📋 Description

• Identify and prioritize AI/ML use cases that deliver measurable business value and ROI. • Develop, validate, and deploy machine learning models for fraud detection, claim risk prediction, customer segmentation, and pricing optimization. • Build and maintain end-to-end data pipelines including data preparation, feature engineering, and model deployment. • Implement advanced analytics techniques, including deep learning, NLP, and computer vision where applicable. • Collaborate with ML Engineers to productionize models using MLOps best practices and CI/CD pipelines. • Ensure compliance with Saudi regulations (PDPL, NDMO) for data usage, model development, and AI governance. • Implement model monitoring, drift detection, and automated retraining pipelines to maintain model performance. • Partner with business stakeholders to translate complex business problems into actionable data-driven solutions. • Conduct A/B testing and experimentation to measure model effectiveness and optimize outcomes. • Develop and deploy explainable AI (XAI) models ensuring transparency and regulatory compliance. • Prepare technical documentation, analytical reports, and executive dashboards on model outcomes and insights. • Lead knowledge transfer sessions and mentor junior data scientists and analysts to build internal capabilities. • Stay current with latest AI/ML research and evaluate new technologies and techniques for business applications. • Collaborate with the Data Engineering team to ensure high-quality, reliable data for ML models. • Support the development of enterprise ML platforms and reusable AI/ML components.

🎯 Requirements

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field (required). • Master’s or PhD in Machine Learning, Data Science, Statistics, or Artificial Intelligence (preferred). • Relevant certifications such as Google Cloud ML Engineer, AWS Certified Machine Learning, TensorFlow Developer, or Azure AI Engineer are a plus. • 5+ years of proven experience in Machine Learning, Data Science, and Applied Statistics. • Strong expertise in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost). • Proficiency in SQL and experience working with big data platforms (e.g., BigQuery, Spark, Databricks). • Hands-on experience with MLOps tools such as Kubeflow, MLflow, Vertex AI, or SageMaker. • Demonstrated ability to work with structured and unstructured data (JSON, text, images). • Deep understanding of statistical methods, experimental design, and hypothesis testing. • Proven track record in model deployment, monitoring, and lifecycle management. • Familiarity with cloud-native ML platforms (Vertex AI, Azure ML, SageMaker). • Knowledge of AI governance frameworks, explainable AI (XAI), and model interpretability. • Experience with deep learning, computer vision, and natural language processing (NLP). • Knowledge of generative AI, LLMs, and real-time or edge ML deployment. • Strong understanding of Saudi data regulations (PDPL, NDMO, SAMA). • Experience in the insurance or financial services domain (fraud detection, pricing models, claims prediction). • Excellent communication skills to explain complex analytical findings to non-technical audiences. • Strong leadership and mentoring abilities, with experience guiding data science teams.