Senior Data Scientist
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Job Description
Senior Data Scientist responsible for developing ML models and conducting advanced statistical analyses for CIEE's data solutions. Collaborating cross-functionally to deliver actionable insights.
Responsibilities:
- Develop predictive and machine learning models to solve business problems (churn, demand forecasting, segmentation, etc.)
- Conduct advanced statistical analyses and controlled experiments (A/B tests, causal inference)
- Perform exploratory data analysis to identify patterns, trends and opportunities
- Communicate results and recommendations clearly to technical and non-technical stakeholders
- Define evaluation metrics and monitor model performance in production
- Act as a technical reference in data science, guiding best practices and methodologies
- Collaborate with data engineers to ensure the availability and quality of required data
Requirements:
- Bachelor’s degree in Statistics, Applied Mathematics, Industrial Engineering, Computer Science, Information Systems, Computer Engineering, Physics, or related technology/exact sciences. Postgraduate studies or a master’s degree in quantitative fields is a plus.
- Proficiency in Python or R for data analysis and modeling
- Advanced knowledge of statistics (hypothesis testing, regression, distributions, Bayesian inference)
- Practical experience with machine learning algorithms (supervised and unsupervised)
- Ability to design and analyze A/B tests with statistical rigor
- Experience with libraries such as scikit-learn, pandas, numpy, statsmodels, or equivalents
- Communication skills to translate complex results into actionable insights
- Technical leadership and methodology definition skills
- Experience with deep learning (TensorFlow, PyTorch) — desirable
- Familiarity with MLOps tools (MLflow, Kubeflow, or similar) — desirable
- Experience with cloud data platforms (Databricks, Snowflake, BigQuery, or similar) — desirable
- Advanced SQL — desirable
- Experience with data visualization (matplotlib, seaborn, plotly) — desirable
Benefits:
- Inclusion and respect for diversity
- Opportunities for learning and holistic professional development
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