Join a top-ranked Equities and Prime platform where you will expand cross asset positioning analytics and translate signals into impactful client narratives. You will partner with Sales & Trading, Research, Quant Research, and Technology to deliver scalable datasets, insightful publications, and commercial outcomes in a fast-paced, collaborative environment.
Job summary:
As a Vice President within JPMorganChase’s Positioning Intelligence team, you will primarily drive the expansion of our Macro and Cross Asset positioning product-expanding datasets, standardizing methodologies, and building client-facing outputs across rates, commodities, equities, credit, and FX. You will publish high-impact research, engage directly with institutional clients, and partner closely with QR and Technology to productionize analytics and dashboards that drive measurable commercial impact.
Job responsibilities:
- Define and drive the macro cross asset positioning product vision and roadmap; deliver datasets, methodologies, and client-facing outputs across rates, commodities, equities, credit, and FX.
- Build and maintain robust analytics: design signal frameworks (e.g., futures and OTC positioning, prime brokerage, ETFs, options), standardize methodologies, and link signals to major markets.
- Publish high-impact research and tactical notes connecting macro cross-asset positioning dynamics to market drivers, regime shifts, and investable implications for clients.
- Internal cross-pollination and learning: rapidly build fluency in the team’s existing equities-led positioning frameworks, datasets, and publishing cadence so as to help support these and be able to leverage that knowledge to extend methodologies consistently across other asset classes
- Contribute to broader team notes, support wider initiatives, and back up teammates on priority deliverables during peak cycles
- Engage top institutional clients: present findings, gather feedback, and tailor dashboards, reports, and datasets to drive adoption and commercial outcomes.
- Partner with Sales & Trading and Research to shape ideas and risk discussions using positioning context; support client meetings and roadshows.
- Collaborate with Quant Research on model design and validation and with Technology on data engineering, governance, and scalability for reliability and stability.
- Productionize and scale outputs (scheduled reports, alerts, dashboards); mentor junior teammates and codify best practices while fostering a solutions-oriented culture.
Required qualifications, capabilities, and skills:
- 5-7 years of industry experience, including 2+ years in macro research, sales, or trading at a sell side, buy side, or public sector institution, with demonstrable cross asset familiarity.
- Deep understanding of macro markets and cross asset linkages across government rates and curves, commodities, equity index/sector/factors, credit, and FX.
- Experience building positioning/flow analytics (e.g., futures/COT, prime brokerage/short interest, ETF and mutual fund flows, options positioning, factor/CTA/trend proxies).
- Strong analytical and statistical skills with ability to frame hypotheses, run robust back tests, and stress methodology choices.
- Excellent written and verbal communication: convert complex analytics into concise, client-ready narratives; strong presentation skills with senior clients and stakeholders.
- Commercial orientation with ability to align research outputs to client needs, prioritize for impact, and deliver under tight deadlines.
- High-integrity data stewardship, including familiarity with data governance, entitlements, licensing, and internal risk controls.
Preferred qualifications, capabilities, and skills:
- Strong coding skills, especially Python and SQL; ability to write and modify code independently.
- Direct experience integrating and interpreting multi-source datasets (e.g., prime brokerage, exchange, vendor, regulatory disclosures, CFTC/COT, EPFR, TRACE, options feeds) and reconciling conflicting signals.
- Experience building client-facing dashboards or tools (e.g., internal apps, notebooks, or BI platforms).