Data Scientist

Company Brief:

Circlys is a pioneering fintech company revolutionizing traditional monthly financial committees (ROSCA or Jameya), or as we call them Circle. Our innovative, authorized, and secure platform empowers individuals to achieve their financial goals with confidence and ease. With a user base of over 3 million and more than SAR 8 billion in savings facilitated through our platform, Circlys is a market leader driven by innovation, collaboration, and a commitment to operational excellence.

The Data Scientist is responsible for developing and deploying machine learning models, analyzing complex datasets, and generating actionable insights to support business decision-making. The role involves applying statistical analysis, predictive modeling, and data visualization techniques to solve business problems, while collaborating with engineering and cross-functional teams to integrate and optimize data-driven solutions. The ideal candidate combines strong technical expertise in Python, SQL, and machine learning with analytical thinking and the ability to communicate insights effectively to technical and non-technical stakeholders.

• Design, develop, and deploy machine learning models to solve business problems (e.g., forecasting, classification, recommendation systems)
• Perform exploratory data analysis (EDA) to identify trends, patterns, and actionable insights
• Document methodologies, assumptions, and results for reproducibility
• Clean, preprocess, and analyze large, structured and unstructured datasets
• Collaborate with engineering teams to product ionize models and integrate them into existing systems/pipelines
• Build dashboards and visualizations to communicate findings to technical and non-technical stakeholders
• Conduct A/B testing and statistical analysis to evaluate business initiatives
• Monitor model performance in production and iterate/retrain as needed
• Stay current with industry trends, tools, and best practices in data science and ML

• Bachelor’s or master’s degree in data science, Computer Science, Statistics, Mathematics, or a related field
• 2–4 years of professional experience in a data science, ML engineering, or analytics role
• Proficiency in Python or R for data analysis and modeling
• Strong knowledge of SQL and experience working with relational databases
• Hands-on experience with ML frameworks (e.g.,
  scikit-learn
  , Tensor Flow
  , PyTorch, XGBoost)
• Solid understanding of statistics, probability, and experimental design (A/B testing)
• Experience with data visualization tools (e.g., Tableau, Power BI,
  matplotlib/seaborn
  )
• Experience with version control (Git) and collaborative development workflows

• Experience with big data tools (Spark, Hadoop, or similar)
• Familiarity with MLOps practices and tools (MLflow, Airflow, Docker, Kubernetes)
• Exposure to NLP, computer vision, or deep learning applications
• Experience working in Agile/Scrum environments

• Strong communication skills to translate technical findings for non-technical audiences
• Analytical, curious mindset with strong problem-solving ability
• Ability to work both independently and collaboratively across cross-functional teams

Google Professional Data Engineer, Microsoft Azure Data Scientist Associate (DP-100), AWS Certified Machine Learning – Specialty, IBM Data Science Professional Certificate, Certified Analytics Professional (CAP), Tensor Flow Developer Certificate, SAS Certified Data Scientist, Deep Learning Specialization (Deep Learning.AI)