Role description:

We are seeking a skilled and experienced Data Scientist with expertise in time series-based predictive

analysis and strong proficiency in Python & MLOps.

As a Data Scientist, you will be responsible for analysing large datasets, building predictive models, and extracting meaningful insights to drive informed decision- making.

Your focus will be on time series data, leveraging statistical modelling and machine learning techniques to forecast future trends and patterns.

Key responsibilities:

Specific responsibilities include (but not limited to):

 Analyse and pre-process large-scale time series datasets, identifying relevant variables and data cleansing requirements.

 Develop and implement advanced statistical models and machine learning algorithms to perform

predictive analysis on time series data.

 Build and validate forecasting models to predict future trends, patterns, and anomalies in time series data.

 Collaborate with cross-functional teams to understand business requirements and translate them

into actionable data science projects.

 Communicate findings and insights effectively to stakeholders, presenting complex concepts in a

clear and concise manner.

 Stay up to date with the latest advancements in time series analysis, statistical modelling, and

machine learning techniques.

 Collaborate with data engineers to optimize data pipelines and ensure efficient data processing for time series analysis.

 Contribute to the development and improvement of data science methodologies, tools, and frameworks.

Key skills/knowledge/experience:

 The candidate should also have a strong understanding of

 Proven experience in time series analysis and forecasting, preferably in a commercial or industrial setting.

 Strong proficiency in Python, including libraries such as Pandas, NumPy, and scikit-learn for data

manipulation and modelling.

 Solid understanding of statistical modelling techniques for time series analysis, such as ARIMA, SARIMA, or Prophet.

 Experience with machine learning algorithms for time series, such as LSTM, GRU, or XGBoost.

 Proficient in data visualization techniques to effectively communicate insights from time

series data.

 Strong problem-solving skills and ability to handle complex and unstructured data.

 Must be proficient in Agile methodologies, Excellent communication, and collaboration skills with the ability to collaborate effectively in fast-paced, cross- functional teams to deliver data- driven solutions iterative

 Familiarity with SQL and experience in working with relational databases.

 Knowledge of data pre-processing techniques, feature engineering, and model evaluation metrics.

Preferred

o Experience with cloud platforms and distributed computing frameworks, such as AWS, Azure, or Google Cloud.

o Familiarity with big data technologies, such as Apache Spark or Hadoop.

o Knowledge of time series forecasting libraries, such as stats models, ARIMA, XGboost, fbprophet, or TensorFlow.

o Understanding of software development practices and version control systems, such as Git

o Experience with GB energy industry