oracle
Senior Data Scientist
Malomatia Career Site
Baladiyat ad Dawhah, QAT
Full-time
Senior · 6+ years experience
Onsite
Discovered 3 weeks ago
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Free
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Responsibilities
- Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight.
- Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans.
- Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team.
- Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL.
- Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders.
- Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations.
- Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team.
- Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions.
- Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team.Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth.
- Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics.
- Contribute to proposals, scoping, and effort estimation for new data science engagements.
Qualifications
- Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred.
- Deep proficiency in Python for analysis and the scientific stack (pandas, NumPy, scikit-learn, statsmodels) and strong SQL.
- Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques.
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