1. Work Complexity

·         Designs experiments, test hypotheses, and build models.

·         Conducts data analysis and develops moderately complex models using Python (scikit-learn, pandas) and PySpark on the Azure/Fabric platform.

·         Designs experiments, test hypotheses, and build models.

·         Conducts advanced data analysis and complex designs algorithm.

·         Designs experiments, test hypotheses, and build models.

·         Conducts advanced data analysis and highly complex designs algorithm.

·         Applies advanced statistical and predictive modelling techniques to build, maintain, and improve on multiple real-time decision systems.

2. BUSINESS REQUIREMENTS

·         Works with stakeholders to identify the business requirements and the expected outcome. 

·         Works with and alongside business analysts by suggesting other products of interest to the client.    

·         Models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions.

·         Works with stakeholders to identify the business requirements and the expected outcome. 

·         Works with and alongside business analysts by suggesting other products of interest to the client.    

·         Models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions.

·         Leads discovery processes with stakeholders to identify the business requirements and the expected outcome. 

·         Works with and alongside business analysts by suggesting other products of interest to the client.    

·         Models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions.

3. DATA REQUIREMENTS

·         Collaborates with subject matter experts to select the relevant sources of information.

·         Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart devices and geo-location information or social media. 

·         Collaborates with subject matter experts to select the relevant sources of information.

·         Works with IT teams to support data collection, integration, and retention requirements based on the input collected with the business. 

·         Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart devices and geo-location information or social media. 

·         Collaborates with subject matter experts to select the relevant sources of information.

·         Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.

4. ANALYSIS

·         Works with colleagues to solve client analytics problems and documents results and methodologies.

·         Works in iterative processes within a team and validates findings.

·         Performs experimental design approaches to validate finding or test hypotheses.

·         Validates analysis by comparing appropriate samples.

·         Employs the appropriate technique to discover patterns — traditional ML (e.g. XGBoost/LightGBM) for structured data and AI methods (RAG, prompt engineering, Agent orchestration, etc.) for structured and unstructured data.

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·         Solves client analytics problems and communicates results and methodologies.

·         Works in iterative processes with the client and validates findings.

·         Develops experimental design approaches to validate finding or test hypotheses. 

·         Validates analysis by comparing appropriate samples.

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·         Employs the appropriate technique to discover patterns — traditional ML (e.g. XGBoost/LightGBM) for structured data and AI methods (RAG, prompt engineering, Agent orchestration, etc.) for structured and unstructured data.

·         Develops innovative and effective approaches to solve client's analytics problems and communicates results and methodologies.

·         Works in iterative processes with the client and validates findings.

·         Develops experimental design approaches to validate finding or test hypotheses.

·         Validates analysis using scenario modelling.

·         Identifies/creates the appropriate technique to discover patterns — traditional ML (e.g. XGBoost/LightGBM) for structured data and AI methods (RAG, prompt engineering, Agent orchestration, etc.) for structured and unstructured data.

5. Qualification and Assurance (Data Quality)

·         Uses the expected qualification and assurance of the information to quantify the accuracy metrics of the analysis. 

·         Assesses, with the business, the expected qualification and assurance of the information in support of the use case.

·         Defines the validity of the information, how long the information is meaningful, and what other information it is related to.

·         Assesses, with the business, opportunities to enhance the qualification and assurance of the information to strengthen the use case.

·         Defines the validity of the information, how long the information is meaningful, and what other information it is related to.

6. ACCESS MANAGEMENT AND CONTROL

·         Qualifies where information can be stored or what information, external to the organisation, may be used in support of the use case.

·         Works with the data steward to ensure that the information used is in compliance with the regulatory and security policies in place. 

·         Qualifies where information can be stored or what information, external to the organisation, may be used in support of the use case.

·         Works with the data steward to ensure that the information used is in compliance with the regulatory and security policies in place. 

·         Qualifies where information can be stored or what information, external to the organisation, may be used in support of the use case.