Senior Data Scientist, Forecasting

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Requirements:

• Master’s or Ph.D. in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related field.
• 5+ years of experience in data science, with at least 3 years in forecasting or time series analysis.
• Strong background in building and deploying machine learning models, especially in financial contexts.
• Proficiency in SQL, Python or R, with experience using libraries like Pandas, NumPy, StatsModels, Scikit-learn, TensorFlow, or Keras.
• Solid understanding of time series analysis techniques, including ARIMA, exponential smoothing, and machine learning methods like LSTM and XGBoost.
• Strong communication skills for presenting technical findings to non-technical stakeholders.
• Familiarity with financial metrics and KPIs is a bonus.

Responsibilities:

• Develop and refine predictive models for financial forecasting.
• Use time series analysis techniques to build models that predict financial metrics.
• Integrate macroeconomic and financial market data for enhanced forecasting.
• Analyze historical financial data to identify trends and anomalies.
• Collaborate with business leaders for data insights and strategic recommendations.
• Create visualizations to communicate insights effectively.
• Continuously improve and optimize forecasting models.
• Scale models for production deployment.
• Mentor junior data scientists and promote data-driven decision-making.
• Stay updated with the latest in machine learning and financial modeling.