Avolta is the world's leading travel experience player. With a traveler‐centric philosophy and a geographically diverse network, the travel retail and F&B company addresses the needs of up to 2.3 billion passengers each year, with 5,500 outlets in more than 75 countries across six continents. Guided by their Destination 2027 strategy and boosted by their recent combination with travel F&B giant Autogrill, the company is well positioned to realize their ambition to create a Travel Experience Revolution through their many locations at airports, motorways, cruise lines, seaports and railway stations amongst others.PURPOSE OF THE ROLEThe Global Data Senior Analyst will be the data engine powering strategic decisions and operational excellence for Avolta's Commercial Optimization team. Every week, commercial leaders will rely on your analyses to understand business performance, identify opportunities, and make critical decisions across pricing, assortment, promotions, and inventory optimization. You will answer urgent questions from the CCO, uncover hidden insights in data, and ensure our data science models are grounded in business reality. This is a high‐impact, high‐visibility role requiring exceptional analytical horsepower, business acumen, speed of execution, and communication skills. You must be comfortable diving deep into data one moment and presenting findings to C‐suite executives the next. Success depends on technical strength (SQL expert, analytical wizard), business savvy (understands commercial dynamics), and clear communication ability to tell compelling stories with data.RESPONSIBILITIESRecurring Business Analytics & Reporting
Own weekly commercial performance reporting: analyze sales trends, margin evolution, pricing actions, competitive moves, promotional performance across categories, regions, and locationsPrepare concise executive dashboards and commentary for CCO, CFO, and commercial leadership highlighting key trends, anomalies, and actionable insightsConduct deep‐dives on performance variances: investigate why sales/margin are up or down, attributing changes to pricing, volume, mix, competition, or external factorsMonitor KPIs for all four commercial optimization pillars (pricing, assortment, promotions, inventory) and flag issues proactivelyRespond rapidly (within hours to 1‐2 days) to urgent analytical questions from CCO, CFO, regional heads, or commercial leadershipAnalyze competitor pricing data (collected via scraping) to identify competitive gaps, opportunities, and threatsProduce regular competitive benchmarking reports: Avolta vs. key competitors by category, location, and pricing strategyAlert commercial teams to significant competitor moves (major price changes, promotions, assortment shifts)
Data Support for Data Science & Strategy
Partner with Lead Data Scientists to provide clean, high‐quality datasets for model development (pricing models, demand forecasts, assortment optimization)Conduct exploratory data analysis (EDA) to identify data quality issues, outliers, and patterns before modelingValidate data science model outputs against business logic and historical performance; flag anomaliesSupport A/B test analysis: prepare test/control groups, track KPIs during experiments, calculate statistical significanceProvide analytical support for strategic initiatives led by Senior Strategy Manager or Principal TPMBuild financial models and scenario analyses for business cases (ROI calculations, sensitivity analysis, payback period)Identify and document data quality issues (missing data, inconsistencies, incorrect mappings) impacting analysis or modelsWork with IT, BI teams, and data engineers to resolve data issues and improve pipelinesMaintain data dictionaries and documentation for key datasets used by team
Insight Generation & Proactive Analysis
Proactively surface insights and opportunities from data exploration (don't just answer questions - identify what questions should be asked)Conduct regular "health checks" on business performance, flagging issues before they escalatePresent findings to commercial teams (category managers, regional leads, merchandising) in weekly or monthly forumsCreate clear, actionable data visualizations (charts, dashboards) that tell stories and drive decisionsTranslate complex analysis into simple business language without losing nuanceBuild self‐serve dashboards (Tableau, Power BI) empowering commercial teams to explore data independently
WHAT WE ARE LOOKING FOR
Expert SQL: writes and optimizes complex queries (CTEs, window functions, subqueries) on large datasetsAdvanced Excel: pivots, INDEX/MATCH, complex formulas; VBA automation a plusPython or R (plus) for data manipulation and analysis beyond ExcelStrong statistical foundation: descriptive stats, regression, hypothesis testing; validates results against business logic5–8 years' experience in commercial analytics, BI, or FP&A within retail, e‐commerce, travel, hospitality, or FMCGDeep commercial understanding: pricing, margins, promotions, inventory, merchandising, and P&L mechanicsInsight‐driven analyst: translates complex data into actionable business recommendationsFinancial analysis expertise: P&L performance, variance analysis, and financial modelingExecutive‐level communication: confident presenting to CCO/CFO and handling challengeClear written communication: concise executive summaries, analytical memos, dashboard commentaryStrong data visualization: creates clear, decision‐ready charts without overcomplicationAudience‐aware communicator: adapts message for executives, commercial teams, and technical stakeholdersBias for speed and ownership: delivers high‐quality analysis in hours/days, not weeksResilient under pressure: thrives with tight deadlines and last‐minute senior requestsSound business judgment & curiosity: focuses on what matters, makes pragmatic assumptions, and probes root causesFluency in English (written & spoken)
Preferred Qualifications
Bachelor's degree in quantitative field (Economics, Finance, Engineering, Mathematics, Statistics, Business Analytics) or equivalent practical experienceExperience with BI tools (Tableau, Power BI, Looker) - can build dashboards, not just consume themPrevious exposure to data science or ML projects - understands enough to support DS teams and validate outputsBackground in pricing analytics, revenue management, or merchandising analytics would be a plusPython proficiency is a plusHaving a background in management consultancy or tech company would be preferred
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