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
