Olajumoke Medunoye
HR Analyst · People Analytics Professional
Turning workforce data into decisions
HR & People Analytics · Leeds, UK
HR Analyst & People Analytics Professional
Turning workforce data into decisions. I build dashboards, forecasting models, and analytics solutions that help organisations understand attrition, plan headcount, and measure what matters.
About Me
I'm an HR and People Analytics professional based in Leeds, UK, with an MSc in Human Resource Management and professional accreditations from CIPD and MHRAP.
My work sits at the intersection of HR strategy and data. I build dashboards, forecasting models, and reporting solutions that give HR teams and leadership the visibility they need to make informed decisions on workforce planning, retention, and performance.
Technically, I work across Power BI, SQL/PostgreSQL, Excel, and Python, with HRIS experience in both Workday and SAP SuccessFactors. I've delivered projects spanning attrition modelling, recruitment analytics, capacity planning, and operational performance reporting.
I'm currently open to remote and hybrid HR Analytics and People Analytics roles across the UK and internationally.
Areas of Focus
Technical Skills
By the Numbers
Hidden annual turnover costs identified using a cost-of-attrition model across departments.
Reduction in executive reporting time through automated Power BI dashboards replacing manual extracts.
Days time-to-hire reduced by identifying bottlenecks in the recruitment pipeline through data analysis.
Reduction in ticket response time through operational workflow analysis and process redesign.
Decrease in employee turnover at Tangerine Africa through targeted, data-informed HR interventions.
Portfolio
Each project below includes a detailed case study. These are end-to-end analytics solutions — from data modelling to dashboard delivery and business recommendations.
Applied a cost-per-departure formula across salary, recruitment, and onboarding data to surface £312K in annual hidden turnover costs tied to 22% attrition. Segmented workforce by tenure, department, and performance band to identify the highest-risk employee groups.
Mapped the full recruitment funnel to identify where candidates dropped out and where delays concentrated. Analysis revealed a shift toward internal recruitment could cut external hiring costs by up to 96%. Time-to-hire fell from 36 to 14 days following process changes.
Consolidated productivity and performance rating data across departments into a single reporting view. Built to allow managers to filter by team, performance band, and time period — enabling identification of underperforming pockets and tracking improvement over quarterly review cycles.
Analysed interaction data across high-volume service operations to identify workflow bottlenecks driving resolution delays. Changes implemented after the analysis reduced average ticket response time by 30% and supported a 95% customer satisfaction rate.
Built scenario models covering growth, steady-state, and reduction cases, allowing leadership to stress-test resourcing decisions. Identified two departments carrying structural understaffing risk that wasn't visible in standard headcount reports.
Used Python to build a classification model on workforce data — tenure, engagement scores, performance ratings, manager changes — outputting risk scores integrated into a Power BI dashboard. Designed to allow HR business partners to prioritise retention conversations based on evidence rather than instinct.
Career
Education & Certifications
Get in Touch
I'm currently open to remote and hybrid HR Analytics and People Analytics roles across the UK and internationally — including NGOs, HR tech, fintech, and the public sector. If you're hiring or want to discuss a project, I'd like to hear from you.
