Bu ilan Shell Petrol A.Ş'nin, Open Resourcing (Açık İstihdam) sisteminin Global Workday alt yapısı çerçevesinde güncellenmesi sonrası erişiminin olmaması nedeniyle Shell Petrol A.Ş. çalışanlarının ilanlara başvuru yapabilmesi için özel olarak yayımlanmıştır.
Paylaşılacak ilan linkleri Shell Çalışanları dışında 3. Şahıslar ile paylaşmamanız şirket içi bilgilerin gizliliği açısından çok büyük önem taşımaktadır.
İlan Tanımı
Job Family Group: Retail Network
Management Level: 04
Present Company: Shell Petrol A.Ş
Country/Region of Work Location: Türkiye
Target Hire Date: 1.04.2026
Worker Type: Regular
Posting End Date: 23.03.2026
Location: Istanbul - Esentepe
Posting Date: 13/03/20256
Job Family: Retail
Time Type: Full time
Job Type: Regular
Supervisory Organization: Murat Kocavelioğlu
Job Description:
Role Purpose
This role shapes customer-centric growth strategy through advanced analytics, behavioural insight, and structured problem solving. It integrates data across fuel, non-fuel retail, loyalty and EV to drive strategic decision-making, customer lifetime value growth and commercial performance. Ideal candidates combine strong analytics (SQL, Python) with a strategy-consulting mindset (structured thinking, hypothesis-driven problem solving, executive storytelling).
Key Responsibilities
1) Customer & Retail Analytics
Analyse customer behaviour and transactional data to detect patterns, trends and performance drivers across fuel, loyalty and non-fuel retail categories.
Conduct segmentation studies, loyalty program performance reviews, promotional uplift analysis and customer lifecycle insights.
Support A/B testing, pricing experiments, and elasticity modelling with data-driven recommendations.
Quantify CLTV, identify high-value pools, churn risk, and cross-sell opportunities.
2) Strategic Problem Solving & Commercial Insight (Strategy Consulting Expectations)
Lead structured, hypothesis-driven analysis to diagnose root causes and quantify value opportunities.
Develop strategic recommendations for pricing, loyalty mechanics, CVP design, promotions and network using evidence-based modelling.
Craft executive-ready storylines and influence senior stakeholders with clear options, trade-offs and prioritised action plans.
3) Data Management & Reporting
Build and maintain analytical datasets, dashboards, KPIs and reporting frameworks for commercial and retail teams.
Use SQL and Python to extract, clean, verify and transform customer and sales data from various sources.
Ensure high data quality, consistency and governance across customer and transactional databases.
Automate repetitive analyses and democratize insights through scalable reporting (Power BI, Tableau).
4) Cross-Functional Collaboration
Partner with marketing, retail operations, CRM, pricing, network, and EV teams to embed insights into strategic and operational decisions.
Serve as the customer analytics focal point supporting priority commercial initiatives across Mobility.
Translate complex analytics into clear, actionable recommendations for non-technical stakeholders.
5) Continuous Improvement & Capability Building
Stay informed about emerging customer analytics techniques, retail data applications, and loyalty optimization approaches.
Introduce new analytical methods (predictive modelling, clustering, experimentation frameworks).
Uplift data literacy and analytical maturity across commercial teams.
Required Qualifications
Experience
JG5: Minimum 3 years in customer analytics, retail analytics, CRM insights or related data roles.
JG4: 6–10 years including exposure to strategy consulting, commercial strategy or advanced analytics leadership.
Technical Skills
Proficiency in SQL for data extraction and querying.
Hands-on Python for data cleaning, analysis, modelling and automation.
Experience with Power BI/Tableau and handling large, complex datasets across digital and customer systems.
Business & Strategy Skills
Strong analytical mindset; ability to interpret complex datasets and deliver clear insights.
Understanding of fuel/retail performance drivers, customer behaviour patterns and loyalty mechanics.
Strategy-consulting capabilities: structured thinking, hypothesis-driven analysis, synthesis, and stakeholder influence.
Excellent communication and executive storytelling tailored for senior management.
Preferred
Background in loyalty analytics, segmentation, fuel retail economics or customer value modelling.
Experience with Databricks or cloud-based data environments.
Familiarity with experimentation platforms and statistical testing.
