Reward Data Science Analyst

at  Lloyds Banking Group

End Date
Thursday 07 November 2024
Salary Range
£0 - £0
We support flexible working – click here for more information on flexible working options
Flexible Working Options
Hybrid Working, Job Share
Job Description Summary
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Job Description
JOB TITLE: Reward Data Science Analyst

Your purpose is to decipher complex data, uncover trends, and deliver actionable insights to stakeholders

• Your foremost responsibility is to conduct thorough and insightful data analysis. You extract, clean, and transform Reward and wider relevant HR data, deriving significant insights to drive evidence-based decision-making.
• Conduct rapid data analysis to extract insights from HR datasets, identifying trends, anomalies, and opportunities for optimisation.
• Generate reports, presentations, and visualisations that effectively convey data-driven insights to non-technical stakeholder

Responsibilities:

• Data Analysis and Modelling: Conduct in-depth analysis of Reward and HR data to identify trends, patterns, and opportunities for improvement.
• Build and refine predictive models to forecast workforce dynamics and attrition risk.
• Algorithm Development: Create innovative machine learning algorithms to optimise our Total Reward offering in line with market benchmarks and personalising to specific role types.
• Continuous Improvement: Stay abreast of the latest data science techniques and trends, continuously enhancing the bank’s HR analytics capabilities.
• Perform exploratory data analysis on Reward and HR datasets to uncover trends and anomalies.
• Use visualisation tools and techniques to provide user friendly insight to help answer specific questions.
• Providing accurate and insightful data analysis to support the strategy of the team.
• Create and evolve tools, dashboards and models to drive decision making on key Reward topics.
• Collaborate with HR teams to understand use cases before designing and implementing innovative solutions
• Lead efforts to enhance data quality, integrity, and security within Reward data sources