Maven - Market Data Manager

• AI, Automation & Operational Tooling • Ownership of the AI and automation roadmap for the Market Data function, deciding what to build, what to buy, and what to outsource; • Daily use of LLMs and AI tooling for vendor analysis, contract digestion, usage analytics, and entitlement audit, with a track record of replacing manual workflows with AI-augmented equivalents; • Use of internal tooling in Python (usage dashboards, automated entitlement reconciliations, simple AI integrations), working adjacent to engineering rather than as engineering; • Automation of monthly reporting, exchange audit workflows, and other repetitive tasks across the Market Data function; • Ownership of MD data ingestion into Maven's central data team infrastructure, enabling easy access and inventory management firmwide. • Vendor Analytics & Commercial Support • Day-to-day ownership of vendor analytics: usage, ROI, redundancy, and renewal forecasting across the full Market Data vendor portfolio; • Support on vendor negotiations, renewal strategy, and RFP processes with major data and exchange vendors (e.g., Bloomberg, LSE/Refinitiv, ICE, CME); • Building of forecast and ROI models to optimise spend and inform future Opex planning; • Identification of opportunities for cost optimisation, vendor consolidation, and improved service levels; • Evaluation and operational assessment of alternative data sources (e.g., sentiment, satellite, web-scraped) to support discretionary and systematic strategies. • Data Inventory & Operational Excellence • Build-out and ownership of Maven's data catalogue and central inventory, raising its profile with business users as the canonical reference for data sets in use across the firm; • Management of day-to-day Market Data operations across Europe, US, and Asia jurisdictions, including monthly data reporting, annual licensing, and exchange audits; • Onboarding of new quant and discretionary data sets across the business, including those required to support the onboarding of new Portfolio Managers, with entitlements, governance, and inventory records in place from day one; • Partnership with the Vendor Strategy function on the cross-firm contract repository, ensuring MD records are accurate, complete, and accessible; • Implementation of operational controls, documentation, and process improvements as the function scales. • People Management & Cross-Functional Partnership • Line management and structured mentorship of Maven's Data Licensing Administrator, including ownership of his development plan and growth path; • Coordination of Market Data-related communication across Trading Desks, Technology/Engineering, Legal, Compliance, and Finance; • Governance, Risk & Compliance • Ensuring compliance with all Market Data licensing obligations, regulatory requirements, and internal governance standards; • Management of entitlements, access, and audit exposure across the Market Data vendor estate; • Deep understanding of Maven's use and interaction with all types of data, ensuring appropriate controls and documentation are in place. • Candidate Specifications: • Between 4 and 8 years' experience gained within market data at a proprietary trading firm, hedge fund, exchange, data or technology vendor, or similar; • Demonstrable track record of using AI and LLM tooling to multiply the throughput of a small team, including replacing manual workflows with automated or AI-augmented equivalents; • Working proficiency in Python, with experience standing up lightweight internal tooling (usage dashboards, automated reconciliations, simple AI integrations); • Breadth across multiple data types (exchange, alternative, and fundamental) sufficient to operate across a multi-strategy book; • Commercial literacy in vendor negotiation, renewal strategy, and RFP discipline; • Experience with market data inventory and management platforms (e.g., TRG Screen, Alveo) or equivalent; • Experience working across multiple regions, time zones, or jurisdictions an advantage. • Knowledge: • Strong knowledge of market data policy and licensing, plus at least one of the following key areas: • ◦     AI and LLM tooling applied to operational workflows • ◦     Lightweight data engineering and automation (Python, SQL) • ◦     Financial products, particularly equities, futures, and options • ◦     Securities exchanges and exchange relationship management • ◦     Alternative data sourcing and governance • ◦     Vendor analytics, cost optimisation, and procurement