Senior Market Risk & Quant Analytics Architect

Phillips 66; Houston (TX); On-site; USD 160,000 - 196,000; Full time

Benefits offered by this job

VCIP bonus

401k company match

Pension plan

Health, Dental, Vision benefits with H

Well-being programs

Job summary

Phillips 66 is seeking a Sr Market Risk & Quantitative Analyst to join a team that identifies, measures, and reports market risks for commodity trading activities. You will help build risk systems (VaR, stress tests, volume monitoring) and deliver risk insights to trading desks.

Requirements include a STEM/quantitative degree and 5+ years of market risk or Python engineering experience; advanced Python, SQL, and data handling skills are essential.

Qualifications

• 5+ years of market risk/quantitative analysis on trading floor or 5+ years of Python engineering experience.
• Expert Python programming with large data-set management using SQL and other tools.
• Bachelor's degree in STEM/quantitative field; advanced degree preferred.

Responsibilities

• Produce global daily risk reports (VaR, stress tests) and explain drivers of change.
• Build and maintain systems to calculate and publish market risk reporting.
• Provide commodity-level risk coverage and clear risk assessments for desks.
• Collaborate with Product Control and support functions for holistic reporting.
• Support scenario analysis, maintain controls, and advise on policy/regulatory alignment.

Skills

Python

SQL

Data analysis

Communication

Model validation

Machine learning

Education

Bachelor's degree in STEM/quantitative field

Advanced degree in quantitative field

Tools

RightAngle

Allegro

ETRM

Job description

Phillips 66 is seeking a Sr Market Risk & Quantitative Analyst to join a team that identifies, measures, and reports market risks for commodity trading activities. You will help build risk systems (VaR, stress tests, volume monitoring) and deliver risk insights to trading desks.

Requirements include a STEM/quantitative degree and 5+ years of market risk or Python engineering experience; advanced Python, SQL, and data handling skills are essential.