Data Scientist (Saudi National)

About the Role

We are seeking a Data Scientist with at least one year of hands-on experience in data analytics, machine learning, or AI to join our Data & AI team at Tarmeez.

In this role, you’ll work on building and deploying predictive models, LLM-powered systems, and data-driven insights that directly influence business strategy and operational decisions.

You’ll collaborate closely with engineers, analysts, and product teams to bring advanced data science solutions to production and continuously improve our fintech intelligence engine.

Key Responsibility

• Work with business and product teams to define data problems and develop impactful AI/ML solutions.
• Apply machine learning, advanced analytics, and NLP techniques to solve high-value use cases.
• Fine-tune and evaluate LLMs for document intelligence, financial data understanding, and classification tasks.
• Perform feature engineering, model development, and A/B testing to improve model accuracy and reliability.
• Develop and maintain data pipelines, data services and production-grade ML workflows
• Visualize model results and communicate insights clearly to both technical and non-technical stakeholders.
• Stay ahead of emerging tools and trends in AI, LLMs, and generative modeling, and experiment with ways to integrate them into Tarmeez’s products.

Requirements

• Saudi National
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 1+ year of experience applying machine learning, deploying LLM based applications, data engineering or advanced data analysis in a professional or research setting.
• Strong knowledge of Python and data science libraries (pandas, numpy, scikit-learn, etc.).
• Experience in building and evaluating models for classification, regression, or forecasting tasks.
• Familiarity with LLMs and NLP tools (e.g., Hugging Face Transformers, LangChain, OpenAI API, Cohere, Gemini, etc.).
• Solid understanding of SQL, data wrangling, and feature engineering.
• Hands-on experience with data visualization tools such as Metabase, Power BI, or Tableau.
• Strong foundation in statistics, probability, and experimental design.
• Effective communicator with the ability to translate analytical findings into actionable business insights.

Preferred Skills

• Experience deploying ML models intoproduction environments.
• Familiarity with Snowflake, Databricks, or similar data platforms.
• Understanding of MLOps practices and version control (Git).
• Exposure to cloud platforms such as GCP, AWS, or Azure.
• Experience in LLM fine-tuning, embedding models, or prompt engineering.
• Background in finance, credit analysis, or investment analytics is a plus.

Exceptions

All of the above can be ignored if you can demonstrate a proven record of exceptional work, through a GitHub portfolio, research, or deployed projects.