Zycus
Website:
zycus.com
Job details:
Zycus is looking for a motivated and analytical Spend Analyst to support customers in gaining visibility into their procurement spend and identifying opportunities for cost optimization. The role involves working with large and complex datasets, understanding procurement and Source-to-Pay (S2P) processes, analyzing supplier and category spend, and translating data into meaningful business insights.
The ideal candidate is someone with strong analytical and problem-solving skills, attention to detail, and an interest in procurement, data analytics, and AI-powered solutions.
Key Responsibilities
- Analyze procurement and spend data across suppliers, categories, business units, geographies, and other dimensions to identify trends, patterns, and opportunities.
- Support spend data cleansing, validation, classification, and categorization to improve the quality and accuracy of spend analytics.
- Work on supplier data activities such as supplier normalization, duplicate identification, and supplier consolidation analysis.
- Understand and analyze procurement transactions such as purchase orders, invoices, goods/services purchases, and other spend-related data.
- Support the development and maintenance of spend taxonomies and category hierarchies to enable meaningful spend analysis.
- Identify maverick spend, fragmented spend, supplier concentration, and other procurement opportunities through data analysis.
- Prepare spend reports, dashboards, analytical outputs, and management-ready presentations for internal and customer stakeholders.
- Perform data quality checks and investigate anomalies, inconsistencies, and gaps in procurement data.
- Work with senior consultants and customer stakeholders to understand business requirements and translate them into analytical outputs.
- Develop insights and recommendations that can help customers improve spend visibility, sourcing effectiveness, supplier management, and procurement efficiency.
- Support implementation and enhancement of Zycus Spend Management solutions.
- Collaborate with Product, Engineering, Consulting, and Customer Success teams to resolve data and functional issues.
- Continuously develop knowledge of procurement, Source-to-Pay (S2P) processes, spend analytics, and AI-enabled procurement.
AI Skills & Initiatives
- Leverage AI and GenAI tools such as Microsoft Copilot, ChatGPT, and Gemini to improve data analysis, documentation, research, and reporting efficiency.
- Explore opportunities to use AI for data quality checks, spend classification, insight generation, and analytical automation.
- Stay updated on emerging AI capabilities and their application in procurement and spend analytics.
Required Skills & Qualifications
- Bachelor's degree in Engineering, Economics, Finance, Business, Statistics, Mathematics, or a related discipline.
- 0–2 years of experience in analytics, consulting, procurement, business analysis, or a related field. Fresh graduates with strong analytical capabilities are encouraged to apply.
- Strong analytical and quantitative skills with the ability to work with large datasets.
- Good working knowledge of Microsoft Excel; familiarity with SQL, Power BI, Tableau, or other analytics tools is an advantage.
- Basic understanding of Procurement and Source-to-Pay (S2P) processes.
- Strong attention to detail and ability to identify patterns, anomalies, and data quality issues.
- Good problem-solving and logical reasoning skills.
- Strong written and verbal communication skills.
- Ability to work effectively in a team and collaborate with cross-functional and customer-facing stakeholders.
- Demonstrated interest in using AI tools to improve productivity and analytical work.
Good to Have
- Internship or project experience in spend analytics, procurement analytics, business analytics, data analysis, or consulting.
- Exposure to procurement concepts such as Sourcing, Supplier Management, Purchase Orders, Invoicing, Accounts Payable, and Contract Management.
- Familiarity with spend classification, procurement taxonomies, supplier normalization, or data cleansing.
- Exposure to ERP/procurement systems such as SAP, Oracle, Microsoft Dynamics, Coupa, SAP Ariba, Ivalua, GEP SMART, or Zycus.
- Experience with SQL, Power BI, Tableau, Python, or other data analytics tools.
- Knowledge of AI-enabled analytics or intelligent automation.
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