Data Scientist

About the Role:

• We are seeking a highly motivated

  Data Scientist Forecasting

  with a strong passion for energy, technology, and data-driven decision-making. In this role, you will be responsible for developing and refining

  energy load forecasting models

  , analyzing

  customer demand patterns

  , and improving

  forecasting accuracy

  using advanced

  time series analysis

  and

  machine learning techniques

  . Your insights will directly support

  risk management, operational planning, and strategic decision-making

  across the company.
• If you thrive in a fast-paced, dynamic environment and enjoy solving complex

  data science challenges

  , we'd love to hear from you!

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

  .