Tech Stack
CloudIoTPandasPythonScikit-LearnSQL
About the role
- Develop and validate time series forecasting models (ARIMA, Prophet, SARIMA, etc.) for predicting demand, performance, or other business metrics.
- Build and evaluate traditional machine learning models (regression, classification, clustering) for prediction and segmentation tasks.
- Clean, preprocess, and integrate data from diverse sources (SQL databases, APIs, flat files, etc.).
- Collaborate with stakeholders to understand business needs and translate them into analytical solutions.
- Document and present results clearly to both technical and non-technical audiences.
- Work with data and software engineers to develop and maintain production-grade data pipelines and model deployments.
- Monitor and periodically retrain or recalibrate models to ensure long-term performance.
Requirements
- 4+ years of relevant experience in data science or a similar analytical role.
- Strong knowledge of statistics and predictive modeling techniques.
- Practical experience with time series forecasting using traditional methods (ARIMA, SARIMA, ETS, Prophet, etc.).
- Proficient in Python (pandas, scikit-learn, statsmodels, matplotlib, etc.).
- Solid experience with SQL and relational databases.
- Ability to translate business problems into actionable analytical tasks.
- Strong analytical mindset and attention to detail.
- Clear verbal and written communication in English.