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Tier-1 brand, popular mid-level data role, and metro location drive high applicant competition.
Core data science skills are transferable, though payments and pricing domain experience improves fit.
Explicit 5+ years and required Python/SQL/BI increase screening, but payments experience is preferred.
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Design and implement value enablement frameworks to optimize pricing strategies and pre-sales propositions.
Lead development of advanced analytics tools (e.g., ROI calculators, dashboards) using Python, SQL, and BI tools to measure and optimize business performance.
Collaborate with global/regional teams and stakeholders to communicate strategic initiatives and ensure alignment on project roadmaps.
5+ years experience in analytics, data science, pricing strategy, customer success, or related fields; payments industry experience preferred.
Proficiency in Python, SQL, and BI tools such as Tableau or Power BI.
Bachelor’s degree in Data Science, Computer Science, Business Analytics, Economics, Finance, or related field.
Not explicitly mentioned: Notice period requirements.
Experienced in scaling data-driven tools with measurable business outcomes, especially in payments or financial services domains.
Strong technical leadership in analytics, capable of designing advanced visualization and automation solutions.
Skilled in translating complex technical insights into strategic recommendations for both technical and non-technical stakeholders.