About the role

  • Data Scientist utilizing Python and PySpark for demand forecasting. Collaborating with multiple teams to deliver end-to-end solutions while handling machine learning tasks.

Responsibilities

  • Proficiency in **Python and PySpark** for data analysis, machine learning, and **demand forecasting** (regression + time series models)
  • Experience with forecasting models such as **LightGBM/ XGBoost** and classical time series methods (e.g., **ETS/ARIMA**)
  • Strong understanding of the machine learning workflow (**data cleansing, feature engineering, model evaluation, model explainability**)
  • Familiarity with forecasting evaluation metrics (e.g. **MAPE, MAE**) and ability to validate model performance
  • Strong **SQL** skills for managing and querying large datasets
  • Knowledge of data visualization tools (e.g., **Power BI**)
  • Experience with cloud-based technologies such as **Databricks, Azure, or AWS**
  • Strong communication skills — able to explain insights and models to both business and technical teams
  • Ownership and accountability — able to deliver end-to-end solutions, not just analysis
  • Collaboration — able to work effectively with **Data Engineering, Tech, Product, and Supply Chain** teams

Requirements

  • Proficiency in **Python and PySpark** for data analysis, machine learning, and **demand forecasting** (regression + time series models)
  • Experience with forecasting models such as **LightGBM/ XGBoost** and classical time series methods (e.g., **ETS/ARIMA**)
  • Strong understanding of the machine learning workflow (**data cleansing, feature engineering, model evaluation, model explainability**)
  • Familiarity with forecasting evaluation metrics (e.g. **MAPE, MAE**) and ability to validate model performance
  • Strong **SQL** skills for managing and querying large datasets
  • Knowledge of data visualization tools (e.g., **Power BI**)
  • Experience with cloud-based technologies such as **Databricks, Azure, or AWS**
  • Strong communication skills — able to explain insights and models to both business and technical teams
  • Ownership and accountability — able to deliver end-to-end solutions, not just analysis
  • Collaboration — able to work effectively with **Data Engineering, Tech, Product, and Supply Chain** teams
  • **Preferred (Optional) Qualifications:**
  • Exposure to MLOps tools (e.g., **MLflow**, job scheduling)
  • Experience building production pipelines for forecast outputs (daily/weekly runs) and supporting downstream systems
  • Experience in real-time analytics or scheduled processing systems
  • Optimization mindset — able to balance accuracy, business impact, and time constraints

Benefits

  • Clear focus.
  • Diverse Workplace (Our members are from around the world!)
  • Non-hierarchical and agile environment
  • Growth opportunity and career path

Job title

Data Scientist

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

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