Data Scientist - Procurement Analytics

Analysis & Problem Solving 

 

 

 

Analyze large, complex datasets such as demographics; rewards, performance, engagement, talent, learning, organization design etc with business datasets where required  

Analyze large amounts of data to identify trends & patterns to generate insights that help inform Procurement Strategies 

Design & implement experiments to test multiple Hypotheses regarding the effectiveness of Procurement with a view to solving specific problems that bottleneck processes or impede decision-making 

Data Quality & Accuracy 

Ensure Data Quality, accuracy & completeness in all analysis & reports 

Work with Procurement Domain specialists & Data Engineers, IT & Strategic partners to build in relevant decision rules, data quality standards & data security & governance protocols in the Data Lake being developed 

Collaborate with relevant stakeholders to develop an Procurement Data architecture that is reliable & secure 

Process Assurance & Efficiency 

Identify opportunities to streamline and automate Procurement processes to drive process efficiency by leveraging Data & Technology 

Ensure Workflow Based Decision Assets are suitably embedded through the use of new & emergent technologies (AI/ML/RPA) 

Develop Use Cases in priority areas to demonstrate success & replicability 

Modelling & Deployment 

Develop predictive models to identify trends & patterns, forecast outcomes & inform Procurement & Business Decisions around workforce trends & patterns such as turnover rates; retention; engagement; hiring of best-fit talent; workforce planning etc 

Build & deploy AI/ML models to optimize decision-making & drive value  

realization across Talent Attraction; Talent Sustainability & Talent Development  

Dashboards & Visualization 

Create Data Visualizations and Dashboards to communicate correlational insights & recommendations to Procurement & Business Leaders 

Build Visualizations using both flat & hierarchical datasets with suitable drill-down functionality to present an aggregate, team & individual view 

Develop views that are customizable for multiple stakeholders: Procurement, Business, COE, Employee, Leadership etc 

Productization 

Explore application of new & emergent technologies such as Generative AI & ML to enhance employee experience 

Collaborate with internal stakeholders & Technology teams to productize innovative ideas that have the potential to drive assurance, enhance experience or improve productivity & process efficiency 

Drive adoption of new models that get developed across the GCC & Business 

Capability Development 

Support to build capability around mindset, analytical approaches & tools/technologies that enable data-driven decision-making 

Support in co-creating relevant use cases across different Procurement verticals  

Support in developing relevant case studies post successful deployment 

3+ years of experience in data analysis, modelling, data mining & visualization 

 

Education Qualification 

Bachelor’s degree in engineering (Computer Science preferred)/Data Science & master’s in management 

Professional certification in related areas is an advantage (Power BI, SQL, Python/R, Tableau) 

Professional certification in Advanced Analytics 

 

Behavioural Skills 

Exceptional analytical mindset & problem-solving approach 

Strong communication skills 

Strategic thinking and decision-making capabilities 

High level of collaboration & stakeholder management 

Quick responsiveness with respect for SLA’s 

High level of Resilience 

Technical Skills 

Certifications in Google Analytics & any Business Analytics certification 

Experience in implementing People analytics and data-driven decision-making 

Analytical & problem-solving skills 

Data & statistical modelling ability 

Good Project Management skills 

Non-Negotiable Skills 

Exceptional Analytical mindset & problem-solving approach 

Demonstrated 3+ years solid experience in People Analytics 

Proven ability around Dashboarding & Visualization tools  

Worked with large & complex Datasets