Data Scientist | FIS Global Negotiation Guide
Negotiation DNA: NYSE: FIS Total Issuing Pure-Play FinTech Banking & Capital Markets Data & Analytics IC Track
| Region | Base Salary | Stock (RSU/4yr) | Bonus | Total Comp |
|---|---|---|---|---|
| Jacksonville FL | $135,000-$175,000 | $60,000-$130,000 | $16,000-$28,000 | $211,000-$333,000 |
| New York | $160,000-$205,000 | $80,000-$180,000 | $22,000-$36,000 | $262,000-$421,000 |
| London | £90,000-£125,000 / $113,000-$156,000 | £45,000-£95,000 / $56,000-$119,000 | £12,000-£22,000 / $15,000-$28,000 | £147,000-£242,000 / $184,000-$303,000 |
Negotiation DNA
Data Scientists at FIS sit atop one of the richest transaction datasets in global financial services. FIS processes billions of transactions annually across banking, capital markets, and payment networks, generating the kind of data density that data scientists at consumer tech companies can only dream about. Following the $24B Worldpay stake sale in January 2026, FIS is channeling this data advantage into its Pure-Play FinTech strategy — using advanced analytics, predictive modeling, and machine learning to power the Total Issuing platform's fraud detection, credit decisioning, and real-time risk scoring capabilities.
The Pure-Play FinTech transformation means FIS is investing heavily in data science as a competitive differentiator. With $500M in incremental cash flow available post-Worldpay divestiture, the company is building out data science teams that can transform raw transaction data into intelligent platform features — real-time fraud scoring, dynamic interchange optimization, predictive customer lifetime value modeling, and automated compliance monitoring. Data Scientists who can bridge the gap between statistical rigor and production-grade model deployment are particularly valuable.
FIS's $13.5B acquisition history created fragmented data estates across dozens of legacy systems — each with its own schemas, data quality issues, and business logic. The Data Scientist who can navigate this complexity, extract signal from noisy cross-system data, and build models that work across FIS's heterogeneous technology landscape holds significant leverage. The Total Issuing platform's success depends on the quality of its data-driven features, making data science a strategic investment priority.
Level Mapping:
| FIS | Meta | Stripe | JPMorgan | Fiserv | |
|---|---|---|---|---|---|
| Data Scientist | DS L4 | Data Scientist (IC4) | Data Scientist | Quantitative Associate | Data Scientist |
| Senior Data Scientist | DS L5 | Data Scientist (IC5) | Senior Data Scientist | Quantitative VP | Senior Data Scientist |
| Staff Data Scientist | DS L6 | Data Scientist (IC6) | Staff Data Scientist | Quantitative ED | Principal Data Scientist |
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Lever 1 — Transaction Data Moat: "FIS processes billions of financial transactions annually, and the $24B Worldpay stake sale in January 2026 refocused the company's data strategy entirely on banking and issuing data — the highest-value data in financial services. As a Data Scientist building models on this dataset, I'm working with data that is orders of magnitude richer than what's available at most tech companies. I'd like my compensation to reflect the Pure-Play FinTech premium for this data access: $200,000-$205,000 base in New York with an RSU grant of $160,000-$180,000 over four years."
Lever 2 — Total Issuing Intelligence Layer: "The Total Issuing platform's competitive differentiation depends on its intelligence layer — real-time fraud scoring, dynamic authorization rules, and predictive analytics. As the Data Scientist building this layer, I'm creating the features that determine whether Total Issuing wins or loses against Marqeta, Lithic, and Stripe Issuing. I'm asking for top-of-band compensation because this is platform-defining data science, not incremental analytics."
Lever 3 — $500M Data Infrastructure Investment: "FIS has $500M in incremental cash flow to invest post-divestiture, and I understand a significant portion is earmarked for data and analytics infrastructure. I'd like my RSU grant to reflect the scale of this investment — $130,000-$180,000 over four years — and I'd like to discuss a data science tooling budget of $15,000-$20,000 annually to ensure I have access to the compute and platforms needed to deliver production-grade models."
Lever 4 — Cross-Acquisition Data Unification: "FIS's $13.5B in acquisitions left behind fragmented data estates with inconsistent schemas and business logic. The Data Scientist who can unify these data sources into a coherent analytics layer for Total Issuing is solving a problem worth tens of millions in data engineering costs. I'd like a $20,000-$25,000 signing bonus to reflect the immediate value I'll bring to the data unification effort as part of the Pure-Play FinTech transformation."
Negotiate Up Strategy: Open at $205,000 base (New York) or $175,000 base (Jacksonville) with a $180,000 RSU grant over four years and a $25,000 signing bonus. Anchor to the transaction data advantage — FIS's data moat is its most defensible asset, and the data scientists who monetize it through Total Issuing intelligence features are creating outsized value. Frame the role as Pure-Play FinTech data science, not enterprise BI. Target 18-22% total comp increase over initial offer. Accept-at floor: $160,000 base (NYC) / $135,000 base (JAX) with at least $80,000 in RSUs. If cash comp is firm, negotiate for a dedicated GPU/compute budget and guaranteed conference attendance for NeurIPS/ICML.
Evidence & Sources:
- FIS 2026 Annual Report — Data analytics strategy and Total Issuing intelligence platform overview
- FIS Investor Day 2026 — $500M incremental cash flow allocation to data and technology
- Levels.fyi — Data Scientist compensation at FIS, Stripe, JPMorgan, and Google (2025-2026)
- Bloomberg — "FIS Pivots to Pure-Play FinTech After $24B Worldpay Stake Sale" (January 2026)
- Glassdoor — FIS Data Scientist salary data across Jacksonville, New York, and London
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