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Tier-1 brand, mid-level data scientist title, generalist analytics skills, and metro hiring increase applicant competition.
Core analytics skills are transferable but payments and pricing domain knowledge increases specialization.
Mandatory 5+ years and technical Python/SQL/BI requirements make shortlisting moderately strict.
Design and implement value enablement frameworks to optimize pricing strategies and customer success metrics.
Develop and lead analytics tools including ROI calculators and dashboards using Python, SQL, and BI tools to measure and enhance business performance.
Collaborate with global and regional teams to deliver data-driven insights and drive strategic initiatives, providing mentorship and stakeholder communication.
5+ years of experience in analytics, data science, pricing strategy, customer success, or related fields; experience in payments industry strongly preferred.
Proficient in Python, SQL, BI tools (Tableau, Power BI), Microsoft Excel, and PowerPoint.
Bachelor’s degree in Data Science, Computer Science, Business Analytics, Economics, Finance, or related field.
Work Experience Required: Minimum 5 years as stated
Experienced in developing scalable data-driven tools with measurable business impact, especially in pricing and customer success contexts.
Strong technical skills with proven ability to apply advanced analytics and visualization in a cross-functional, global business environment.
Able to lead strategic projects with clear communication to both technical and non-technical stakeholders and provide team mentorship.