Job Description:

Key responsibilities:

1. Modeling & Machine Learning

• Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems).
• Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.).
• Work on feature engineering, model interpretability, and performance optimization.

2. Data-Driven Business Strategy

• Partner with stakeholders to identify key opportunities where data science can drive business value.
• Translate business problems into data science projects with clearly defined deliverables and success metrics.
• Provide actionable recommendations based on data analysis and model outputs.

3. Analytics and Experimentation

• Conduct deep-dive exploratory analysis to uncover trends and insights.
• Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness
• Design and analyze A/B tests and other experiments to support product and marketing decisions.
• Automate data pipelines and dashboards for ongoing monitoring of model and business performance.

Technical Skills:

• Languages: Proficient in Python, MySQL.
• Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch.
• Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis
• Databases : PostgreSQL, BigQuery, MySQL.
• Visualization: Plotly, Seaborn, Matplotlib.
• Deployment: Experience in Gitlab, CI/CD pipelines(Good to have).
• Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have).

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