About the Role:
- We are seeking a highly motivatedData Scientist Forecastingwith a strong passion for energy, technology, and data-driven decision-making. In this role, you will be responsible for developing and refiningenergy load forecasting models, analyzingcustomer demand patterns, and improvingforecasting accuracyusing advancedtime series analysisandmachine learning techniques. Your insights will directly supportrisk management, operational planning, and strategic decision-makingacross the company.
- If you thrive in a fast-paced, dynamic environment and enjoy solving complexdata science challenges, we'd love to hear from you!
Key Responsibilities:
- Develop and enhanceenergy load forecasting modelsusingtime series forecasting,statistical modeling, andmachine learning techniques.
- Analyze historical and real-timeenergy consumption datato identify trends and improve forecasting accuracy.
- Investigate discrepancies betweenforecasted and actual energy usage, providing actionable insights.
- Automatedata pipelinesandforecasting workflowsto streamline processes across departments.
- Monitor day-over-dayforecast variationsand communicate key insights to stakeholders.
- Work closely with internal teams and external vendors to refineforecasting methodologies.
- Performscenario analysisto assess seasonal patterns, anomalies, and market trends.
- Continuouslyoptimize forecasting models, leveraging techniques likeARIMA, Prophet, LSTMs, and regression-based models.
Qualifications & Skills:
- 3-5 years of experiencein data science, preferably inenergy load forecasting, demand prediction, or a related field.
- Strong expertise intime series analysis,forecasting algorithms, andstatistical modeling.
- Proficiency inPython, with experience using libraries such aspandas, NumPy, scikit-learn, statsmodels, and TensorFlow/PyTorch.
- Experience working withSQLand handling large datasets.
- Hands-on experience withforecasting modelslikeARIMA, SARIMA, Prophet, LSTMs, XGBoost, and random forests.
- Familiarity withfeature engineering, anomaly detection, and seasonality analysis.
- Strong analytical and problem-solving skills with adata-driven mindset.
- Excellent communication skills, with the ability totranslate technical findings into business insights.
- Ability to work independently and collaboratively in afast-paced, dynamic environment.
- Strong attention to detail, time management, and organizational skills.
Preferred Qualifications (Nice to Have):
- Experience working withenergy market data, smart meter analytics, or grid forecasting.
- Knowledge ofcloud platforms (AWS)fordeploying forecasting models.
- Experience withbig data technologiessuch asSpark or Hadoop.
