Data Scientist at malomatia in Doha, Qatar, Qatar

The Data Scientist is responsible for producing clean, well-documented, and reproducible analytical work and for communicating results clearly to both technical colleagues and business stakeholders. It is an ideal role for someone who enjoys working closely with data, iterating on models, and turning raw datasets into actionable insight.

Must Have

• 3–5 years of experience in data science, analytics, or a quantitative modeling role.
• Hands-on proficiency in Python (pandas, NumPy, scikit-learn) and SQL for building and evaluating models end to end.
• Demonstrated ability to design experiments, validate model performance, and guard against overfitting and data leakage.
• Clear, reproducible, and well-documented analytical practice.
• Ability to communicate findings clearly to both technical colleagues and business stakeholders.

Nice to Have

• Experience with visualization tools such as matplotlib, seaborn, Power BI, or Tableau.
• Exposure to cloud analytics environments, ideally Oracle Cloud Infrastructure (OCI).
• Experience with time-series analysis or natural-language data.
• Familiarity with collaborative workflows and code review.
• Exposure to working with engineering teams on model handoff.
• Data science certifications.

Responsibilities

• Conduct exploratory data analysis to uncover patterns, relationships, and opportunities in client and operational data.
• Build, train, and evaluate predictive and descriptive models using Python (pandas, scikit-learn) and SQL.
• Build and evaluate deep learning models, such as neural networks, using frameworks like TensorFlow or PyTorch where they suit the problem.
• Perform feature engineering, data cleaning, and dataset preparation for modeling.
• Design and analyze experiments, including A/B tests, to measure the impact of changes and interventions.
• Prototype analytical solutions and iterate on them based on stakeholder and senior data scientist feedback.
• Create clear visualizations, dashboards, and summaries that translate analysis into business insight.
• Validate model performance using appropriate metrics and guard against overfitting and data leakage.
• Document methodology, assumptions, and results to ensure reproducibility and knowledge sharing.
• Collaborate with senior data scientists, engineers, and analysts on larger initiatives.
• Support the preparation of analytical reports and presentations for clients and internal teams.
• Maintain and improve existing analytical code and notebooks

Qualifications

• Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, Data Science) or equivalent experience; Master's an advantage.
• Proficiency in Python for data analysis (pandas, NumPy, scikit-learn) and working knowledge of SQL.
• Solid grounding in statistics and core machine-learning techniques (regression, classification, clustering).
• Working knowledge of deep learning concepts and frameworks such as TensorFlow or PyTorch.
• Experience with feature engineering and preparing real-world, messy datasets for modeling.
• Ability to communicate findings clearly to technical and business audiences.
• Understanding of model evaluation metrics and validation techniques.
• Familiarity with version control (Git) and reproducible analysis practices.