Senior Analyst O2C - ECommerce

PERSOL; Bengaluru; On-site; INR 900,000 - 1,300,000; Part time

Job summary

PERSOL is seeking a Senior Analyst – Supply Solutions for Fashion in Bengaluru, India, for a 6-month contract. The role emphasizes accurate PO execution and AI-enabled, data-driven decision support to improve service levels and reduce delays.

You will own the PO lifecycle, publish concise updates, and build scalable KPI views using Power BI or Tableau, plus advanced Excel and SQL skills. 4–6 years in order management or supply chain in retail or fashion is preferred; apparel knowledge is a plus.

Qualifications

• Bachelor’s degree in Commerce, Business Administration, Supply Chain, Engineering, or a related discipline.
• 4–6 years of relevant experience in order management, supply chain, retail, CPG, or a similar environment.
• Advanced Excel and strong working knowledge of SQL for analysis, validation, and insight generation.
• Experience with data visualization tools such as Power BI, Tableau, or equivalent.
• Experience applying AI-enabled methods in operations, planning, or analytics.
• Experience in supplier performance programs and delay recovery governance.

Responsibilities

• Execute weekly ordering for replenishment and non-replenishment purchase orders with strong data accuracy.
• Manage the PO lifecycle, including revisions, status tracking, exception logging, and issue closure.
• Coordinate supply chain interruption updates, including factory constraints, shipment slippages, and recovery plans.
• Publish concise progress updates for business stakeholders with clear decisions, actions, and ownership.
• Maintain SOPs and control documents with disciplined versioning and audit readiness.
• Lead structured problem-solving for supplier delay scenarios, from detection to closure.
• Run cross-functional action plans with sourcing, planning, logistics, and supplier partners to recover at-risk orders.
• Define and track delay recovery playbooks, including alternatives such as re-prioritization, partial allocation, and timeline resets.
• Create and maintain early-warning indicators for supplier performance and delivery risk.
• Drive weekly risk reviews with clear escalations, dependency management, and decision logs.
• Recommend systemic fixes that reduce repeat delay patterns and improve planning reliability.
• Partner with product and technology teams to design, test, and deploy process improvements.
• Coach team members on structured analytics, data interpretation, and exception triage methods.
• Ensure compliance with Walmart policies, data quality standards, and responsible AI usage principles.
• Added Advantage: Apparel and Fashion Domain Knowledge
• Understanding of apparel and fashion supply chain dynamics, including seasonality, lead-time sensitivity, and style-level variability.
• Awareness of fashion lifecycle constraints such as launch windows, trend-driven demand shifts, and markdown risk.
• Ability to interpret supplier and capacity constraints in the context of apparel and fashion planning cycles.

Skills

Supply Chain

PO Management

Supplier Performance

Supply Solutions

Advanced Excel

SQL

Power BI

Tableau

Education

Bachelor’s degree in Commerce/Business/Supply Chain/Engineering

Tools

SQL

Power BI

Tableau

Excel

Job description

Position: Senior Analyst Supply Solutions | Fashion
Contract: 6 Months
Experience: 46 Years
Location: Bengaluru, India
Key Skills: Supply Chain, PO Management, Supplier Performance, Supply Solutions, Advanced Excel, SQL, Power BI/Tableau

Senior Analyst Supply Solutions | Fashion

Function: Supply Solutions
Location: Bengaluru, India
Job Level: Individual Contributor – Senior Analyst

Role Purpose

The Senior Analyst – Supply Solutions is responsible for delivering accurate and timely purchase order execution while elevating the function from transactional processing to AI-enabled, data-driven decision support. The role combines operational discipline, strong analytical judgment, and practical program management to improve service levels, reduce delays, and solve supplier-facing execution risks at scale.

What Success Looks Like

• Order cycles run on time with high transaction quality and clear exception ownership.
• Teams receive proactive, insight-led recommendations rather than passive status reporting.
• Supplier delay risks are identified early, triaged correctly, and resolved through structured action plans.
• AI and automation improve speed, consistency, and quality of operational decisions.
• Cross-functional governance is reliable, transparent, and outcome-focused.

Key Responsibilities

1. Operational Execution and Control

• Execute weekly ordering for replenishment and non-replenishment purchase orders with strong data accuracy.
• Manage the PO lifecycle, including revisions, status tracking, exception logging, and issue closure.
• Coordinate supply chain interruption updates, including factory constraints, shipment slippages, and recovery plans.
• Publish concise progress updates for business stakeholders with clear decisions, actions, and ownership.
• Maintain SOPs and control documents with disciplined versioning and audit readiness.

2. AI and Advanced Analytics – Mandatory

• Analyze demand, forecast, and order signals to detect outliers, risk clusters, and recurring root causes.
• Use AI-assisted tools responsibly for anomaly detection, prioritization logic, and insight generation.
• Develop practical analytical frameworks to separate urgent exceptions from low-impact noise.
• Convert complex analysis into simple business narratives for planners, merchants, and leadership teams.
• Build scalable KPI views and dashboards that improve action speed and accountability.
• Measure and communicate the impact of AI and automation using baseline-versus-outcome metrics.

3. Supply Solutions – Mandatory

• Lead structured problem-solving for supplier delay scenarios, from detection to closure.
• Run cross-functional action plans with sourcing, planning, logistics, and supplier partners to recover at-risk orders.
• Define and track delay recovery playbooks, including alternatives such as re-prioritization, partial allocation, and timeline resets.
• Create and maintain early-warning indicators for supplier performance and delivery risk.
• Drive weekly risk reviews with clear escalations, dependency management, and decision logs.
• Recommend systemic fixes that reduce repeat delay patterns and improve planning reliability.

4. Collaboration and Capability Building

• Partner with product and technology teams to design, test, and deploy process improvements.
• Coach team members on structured analytics, data interpretation, and exception triage methods.
• Ensure compliance with Walmart policies, data quality standards, and responsible AI usage principles.

Added Advantage: Apparel and Fashion Domain Knowledge

• Understanding of apparel and fashion supply chain dynamics, including seasonality, lead-time sensitivity, and style-level variability.
• Awareness of fashion lifecycle constraints such as launch windows, trend-driven demand shifts, and markdown risk.
• Ability to interpret supplier and capacity constraints in the context of apparel and fashion planning cycles.

Required Qualifications

• Bachelor’s degree in Commerce, Business Administration, Supply Chain, Engineering, or a related discipline.
• 4–6 years of relevant experience in order management, supply chain, retail, CPG, or a similar environment.
• Advanced Excel and strong working knowledge of SQL for analysis, validation, and insight generation.
• Demonstrated analytical strength in framing hypotheses, identifying root causes, and driving actions.
• Strong stakeholder communication and program-tracking skills in cross-functional environments.
• Experience with data visualization tools such as Power BI, Tableau, or equivalent.
• Experience applying AI-enabled methods in operations, planning, or analytics.
• Experience in supplier performance programs and delay recovery governance.

Role Expectation

This is not a transaction-only role. The Senior Analyst is expected to combine flawless execution with analytical depth, program management rigor, and practical AI adoption to improve business outcomes.