Principal Data Scientist
1 month ago
Job Description :
We are seeking a highly experienced and accomplished Principal Data Scientist to lead the development and optimization of forecasting models within our organization.
In this role, you will play a critical role in leveraging your expertise in machine learning and data science to build robust, scalable, and accurate forecasting solutions.
You will collaborate effectively with data engineers and other data scientists to translate business needs into technical specifications and deliver impactful results.
Responsibilities :
- Develop, maintain, and optimize machine learning models for forecasting across various business domains.
- Conduct in-depth analysis of historical data to identify patterns and trends that inform model development.
- Select and implement appropriate forecasting algorithms, including time series analysis (ARIMA, Prophet), traditional machine learning (GLM, XGBoost), hierarchical modeling (Top-Down, Bottom-Up), deep learning (Seq2Seq, Transformer), and ensemble methods.
- Continuously evaluate and improve model performance through techniques like hyperparameter tuning and feature engineering.
- Collaborate closely with data engineers to ensure efficient data pipelines and infrastructure for model training and deployment.
- Partner with data scientists and business stakeholders to translate business requirements into clear technical specifications.
- Communicate complex data science concepts and findings effectively to technical and non-technical audiences.
- Stay up-to-date on the latest advancements in forecasting techniques and machine learning algorithms.
- Document and share knowledge to foster a collaborative and innovative data science environment.
- Lead and mentor junior data scientists, providing guidance and support for their professional development.
Qualifications :
- Minimum of 3 years of direct experience building and deploying forecasting solutions using machine learning.
- In-depth knowledge of forecasting algorithms, including time series analysis, traditional machine learning, hierarchical modeling, deep learning, and ensemble methods.
- Proven experience with Python programming language and libraries like NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch.
- Experience working with large volume data and big data processing tools like Apache Spark (PySpark).
- Strong understanding of SQL for data retrieval and manipulation.
- Excellent communication and collaboration skills to work effectively with cross-functional teams.
- Proven ability to translate business problems into actionable data science solutions.
- Strong leadership skills to mentor and guide junior data scientists.
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