Division Manager

We are looking for a business-oriented Data Analytics leader who can bridge data with execution. Unlike a traditional analytics role that focuses primarily on reporting and analysis, this position partners closely with retail business teams and special project leaders to identify business opportunities, generate actionable insights, and translate analytical findings into execution plans that improve business performance. This role will serve as the analytics backbone of the team by simplifying complex data, building analytical models, identifying performance drivers, and enabling project managers to focus on stakeholder engagement, business validation, and execution.

Key Responsibilities

• Business Opportunity Identification: Identify business opportunities and performance gaps through data analysis across retail operations, merchandising, customer, supply chain and strategic projects. Translate business questions into analytical approaches and prioritize high-impact opportunities. Proactively identify where the business should focus next.
• Analytics & Insight Generation: Develop analytical models to identify sales opportunities, range gaps, productivity improvement, customer behavior, store performance and operational bottlenecks. Convert analytical outputs into clear business insights with recommended actions. Support business cases with quantitative evidence.
• Translate Insights into Execution Plans: Work closely with project managers and business stakeholders to transform analytical findings into actionable execution plans. Support initiative design by defining opportunity sizing, success metrics, KPIs, pilot scope and expected impact. Ensure insights are translated into measurable business actions.
• Data Foundation & Analytical Enablement: Develop and maintain reusable datasets, dashboards, SQL scripts and analytical models that enable faster business decision-making. Improve data accessibility for project teams by automating repetitive analysis whenever possible. Act as the team's technical expert in data preparation and analytics.
• Cross-functional Business Partnering: Partner with Merchandising, Operations, Supply Chain, Digital, Finance and other business functions to validate findings and refine recommendations. Facilitate discussions using data as objective evidence to support decision making.
• Strategic Project Analytics: Support strategic transformation initiatives by defining KPIs, tracking benefits realization, measuring pilot performance, evaluating business impact and conducting post-implementation reviews. Provide ongoing analytical support throughout the project lifecycle.
• Coaching & Capability Building: Improve the team's analytical capability by coaching colleagues on interpreting data, asking the right business questions, understanding KPIs and using dashboards effectively. Help establish best practices for data-driven decision making within the team.

Requirements

• 6+ years in Data Analytics, Business Analytics, Strategy, Consulting or Retail Analytics.

• Degree in Industrial Engineering, Supply Chain, Finance, IT or related field.

• Experience working closely with business teams instead of purely technical analytics teams.

• Experience supporting senior management or strategic projects is highly preferred.

• Technical Skills:

• Strong proficiency in SQL (Databricks preferred), Python, and Power BI / Tableau; handling large-scale retail datasets.

• Experience developing analytical models, forecasting, segmentation, hypothesis testing, statistical analysis and automation (Correlation, Regression, etc.).

• Ability to use data and metrics to test theories, back up assumptions, develop business cases, complete root cause analysis and measure success.

• Business Skills:

• Strong business acumen with the ability to connect data to commercial decisions.

• Ability to translate ambiguous business problems into structured analytical frameworks.

• Strong problem-solving mindset with experience identifying root causes and recommending practical business solutions.

• Skilled in process improvement, project management, and data analysis.

• Soft Skills:

• Excellent stakeholder management and presentation skills.

• Strong storytelling using data and ability to simplify complex analysis for non-technical audiences.

• Ability to work independently in a fast-paced business environment with a strong business partnering