Data Scientist

Job Title: Data Scientist Electric Load Forecasting

Location:

Job Type:

Experience:

About the Role:

Data Scientist – Forecasting

data science challenges

Key Responsibilities:

• Develop and enhance

  energy load forecasting models

  using

  time series forecasting

  ,

  statistical modeling

  , and

  machine learning techniques

  . 
• Analyze historical and real-time

  energy consumption data

  to identify trends and improve forecasting accuracy. 
• Investigate discrepancies between

  forecasted and actual energy usage

  , providing actionable insights. 
• Automate

  data pipelines

  and

  forecasting workflows

  to streamline processes across departments. 
• Monitor day-over-day

  forecast variations

  and communicate key insights to stakeholders. 
• Work closely with internal teams and external vendors to refine

  forecasting methodologies

  . 
• Perform

  scenario analysis

  to assess seasonal patterns, anomalies, and market trends. 
• Continuously

  optimize forecasting models

  , leveraging techniques like

  ARIMA, Prophet, LSTMs, and regression-based models

  . 

Qualifications & Skills:

• 3-5 years of experience

  in data science, preferably in

  energy load forecasting

  , demand prediction, or a related field. 
• Strong expertise in

  time series analysis

  ,

  forecasting algorithms

  , and

  statistical modeling

  . 
• Proficiency in

  Python

  , with experience using libraries such as

  pandas, NumPy, scikit-learn, statsmodels, and TensorFlow/PyTorch

  . 
• Experience working with

  SQL

  and handling large datasets. 
• Hands-on experience with

  forecasting models

  like

  ARIMA, SARIMA, Prophet, LSTMs, XGBoost, and random forests

  . 
• Familiarity with

  feature engineering, anomaly detection, and seasonality analysis

  . 
• Strong analytical and problem-solving skills with a

  data-driven mindset

  . 
• Excellent communication skills, with the ability to

  translate technical findings into business insights

  . 
• Ability to work independently and collaboratively in a

  fast-paced, dynamic environment

  . 
• Strong attention to detail, time management, and organizational skills. 

Preferred Qualifications (Nice to Have):

• Experience working with

  energy market data, smart meter analytics, or grid forecasting

  . 
• Knowledge of

  cloud platforms (AWS)

  for

  deploying forecasting models

  . 
• Experience with

  big data technologies

  such as

  Spark or Hadoop

  .