Full-Time Data Scientist

• Data Integration: Combining client data across digital, offline, and emerging channels.
• Model Development: Building MMM using Bayesian regression, regularized regression, and time-series modeling.
• Scenario Simulation: Forecasting outcomes under different budget allocations.
• Deployment & Visualization: Using Streamlit for interactive, client-facing dashboards.
• Scalability: Supporting multiple clients with varying data volumes.

1. Develop and maintain media mix models.
2. Engineer and optimize data pipelines.
3. Design and deploy Streamlit-based dashboards.
4. Conduct EDA and feature engineering.
5. Apply Bayesian methods to improve model accuracy.
6. Implement optimization algorithms.
7. Collaborate with product, engineering, and client teams.
8. Present insights to senior stakeholders.
9. Stay current with emerging techniques.

• Bachelor’s or Master’s in Data Science, Statistics, or related field.
• Experience in media mix modeling or marketing analytics.
• Proficiency in Python (pandas, NumPy, scikit-learn, statsmodels, PyMC).
• Experience with Streamlit or equivalent frameworks.
• Proficiency in SQL.
• Strong foundation in statistical modeling.

• Experience with Bayesian hierarchical models and time-series decomposition.
• Familiarity with cloud platforms (AWS, GCP, Azure).
• Experience with data visualization tools beyond Streamlit.
• Exposure to big data ecosystems (Spark, Hadoop).
• Knowledge of causal inference techniques.

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