Data Scientist

About Circlys

Circlys is a fintech company focused on modernizing traditional monthly financial committees (ROSCA or Jameya) through an authorized and secure platform. The company has facilitated over SAR 8 billion in savings for a user base exceeding 3 million, establishing itself as a market leader in Riyadh, Saudi Arabia.

The Role of Data Scientist

The Data Scientist is responsible for developing and deploying machine learning models, analyzing complex datasets, and generating actionable insights to support business decision-making. This full-time 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 will possess 2-5 years of experience and combine strong technical expertise with analytical thinking and effective communication skills.

Key Responsibilities

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

Required Qualifications and Skills

• 2-5 years of experience in a data science role.
• Strong technical expertise in Python, SQL, and machine learning.
• Analytical and curious mindset with strong problem-solving ability.
• Ability to work both independently and collaboratively across cross-functional teams.
• Strong communication skills to translate technical findings for non-technical audiences.

Preferred Experience and Certifications

• Experience with big data tools such as Spark or Hadoop.
• Familiarity with MLOps practices and tools including MLflow, Airflow, Docker, or Kubernetes.
• Exposure to Natural Language Processing (NLP), computer vision, or deep learning applications.
• Experience working in Agile/Scrum environments.
• Recommended certifications (a plus, not required) include 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), TensorFlow Developer Certificate, SAS Certified Data Scientist, or Deep Learning Specialization (************