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Reward Data Science Analyst
at Lloyds Banking Group Bristol in Bristol (Published at 25-10-2024)
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 . Job Description JOB TITLE: Reward Data Science Analyst SALARY: £45,954 - £51,060 LOCATION: Bristol, Edinburgh, Halifax and Leeds HOURS: Full-time WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites. About this Opportunity Are you a curious data enthusiast with a passion for uncovering insights to inform decision making on Reward strategies for over 60 000 colleagues? Are you keen on identifying and solving customer/collaborator needs through data storytelling? This role within the Total Reward team will play a pivotal role in using advanced data analytics and machine learning techniques to extract significant insights from Diverse HR data sources 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 stakeholders
- 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.
- Data Science Expertise: Profound understanding of advanced data analytics, statistical modelling, machine learning, and data manipulation
- Programming Languages: Proficiency in Python/R and related data science libraries (e.g., NumPy, Pandas, scikit-learn).
- SQL Proficiency: Solid skills in querying and manipulating data from relational databases.
- Data Modelling: Experience in designing and creating optimal data models to streamline FinOps
- Data Visualisation – experience in using a range of tools including PowerBi and Tableau
- Domain Knowledge: Comprehensive understanding of HR processes, policies, and challenges within the banking sector.
- Storytelling & Communication: Excellent verbal and written communication skills to convey complex findings to non-technical collaborators.
- Collaboration: Demonstrable ability to work closely in multi-functional teams and influence decision-making.
- Problem Solving: Creative problem-solving skills to address unique HR challenges using data-driven approaches.
- A generous pension contribution of up to 15%
- An annual performance-related bonus
- Share schemes including free shares
- Benefits you can adapt to your lifestyle, such as discounted shopping
- 28 days’ holiday, with bank holidays on top
- A range of wellbeing initiatives and generous parental leave policies
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