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Celonis is seeking a Lead Value Engineer to drive AI-powered process intelligence adoption across top-tier global financial institutions. This strategic role bridges customer success and technical strategy, positioning you as a trusted advisor to C-suite banking executives (CRO, CIO, CFO, heads of retail/wholesale banking).
You will own the end-to-end customer value journey, from technical discovery and proof-of-concept pilots through quarterly business reviews. Key responsibilities include: translating executive banking priorities into high-impact AI use cases (intelligent credit underwriting, automated fraud mitigation, hyper-personalized wealth advisory); architecting scalable data flows to resolve operational bottlenecks across legacy core banking platforms, payment rails, and loan origination pipelines; building data-backed business cases driving $10M+ in OPEX savings or net-new revenue; automating complex front-to-back office workflows using Lean/Six Sigma methodologies; and delivering value narratives to G-SIB leadership to accelerate software adoption.
Ideal candidates possess 7-10 years of experience navigating unstructured enterprise problems, with a hybrid background bridging institutional financial services and elite business strategy. You should follow one of two trajectories: banker-turned-consultant (risk management, capital markets, or banking operations pivoting to management consulting or SaaS value engineering) or consultant-turned-banking-strategist (MBB, Big 4, or elite tech consultancy background with deep digital transformation portfolio, specialized in retail/commercial banking or fintech).
Non-negotiables include: proven track record in consultative value-selling and enterprise SaaS digital transformations; functional understanding of generative AI, process mining, and their intersection with enterprise financial systems (FIS, Fiserv, Temenos, SAP Banking); deep domain expertise in 2+ areas (credit risk, wealth management, payments, capital markets, ALM, KYC/AML); and strong grasp of financial services risk frameworks, internal controls, and regulatory mandates (Dodd-Frank, Basel III/IV, SEC, FINRA, CFPB).
Education: B.S. or M.S. in Finance, Economics, Financial Engineering, Computer Science, Data Science, or Business Administration. Certifications in Lean Six Sigma Black Belt, advanced data analytics, CFA, or FRM are advantageous. Visa sponsorship is not available.
