Asset and System Analyst at LyondellBasell Industries
Houston, TX 77056, USA -
Full Time


Start Date

Immediate

Expiry Date

28 Nov, 25

Salary

0.0

Posted On

28 Aug, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Economics, Python, Data Science, Storage, Chemical Engineering, Sql, Time Series Analysis, Optimization Techniques

Industry

Information Technology/IT

Description

Location:Houston, TX, US, 77056
Req ID: 88867
Facility: Williams Tower -130
Department: GF&E Strategy and Planning
Division: Olefins and Polyolefins, Refining
LyondellBasell is a leader in the global chemical industry creating solutions for everyday sustainable living. With a nearly 70-year legacy that includes a Nobel Prize in Chemistry and our proprietary MoReTec recycling technology, LYB is enabling a more sustainable future for generations to come. LYB develops high-quality and innovative products for applications ranging from sustainable transportation and food safety to clean water and quality healthcare. LYB places high priority on diversity, equity and inclusion and is Advancing Good with an emphasis on our planet, the communities where we operate and our future workforce. We’re addressing the global challenges of ending plastic waste, taking climate action, and supporting a thriving society, while generating value for our customers, investors, and society.

A DAY IN THE LIFE:

LYB is launching a program called Connected for Value (CfV) under our strategic pillar to Grow and Upgrade the Core to establish and scale the combined capability of Value Chain Optimization and Supply and Trading. This new initiative aims to deliver higher and more resilient integrated margins while expanding our core business capabilities within LYB.
We are seeking a commercially minded and analytically strong Asset and System Analyst to support our Front Office activities. The role is ultimately responsible for facilitating the decision making of our traders through advanced analytics with the source of the data being mainly plant, trading and optimization data.
The ideal candidate will thrive in a fast-paced optimization and trading environment and be able to translate complex data into clear and actionable indicators. This role is distinct from market risk or policy oversight—it is focused on operational optimization decision.

MINIMUM QUALIFICATIONS:

  • 10+ years of experience in petrochemicals or oil/gas optimization, commercial analytics, or trading operations in commodities
  • Bachelor’s degree in Chemical Engineering
  • Tech stack mastery: Python, SQL, cloud data tools (e.g., Databricks), BI (Power BI)
  • Exceptional attention to detail, with an ownership mindset and operational accountability

PREFERRED QUALIFICATIONS:

  • Advanced degree in Data Science
  • Advanced modeling experience: ML/statistics, time-series analysis, pricing or optimization techniques
  • Understanding of commodity logistics, storage, and blending economics
Responsibilities
  • Commercial Optimization Metrics
  • Automate storage of production optimization planned results into Data Bricks that can be later compared to actual plant performance
  • Create and own dashboards that show the commercial impact of Planned vs Actual Results
  • Understand trading strategy P&L and develop strategy metrics
  • Partner with LP Analysts and Traders to explain variances

    1. LYB Commodity Logistic Analytics
  • Develop and maintain live logistic dashboards with show economic optimization for various commodities and pipeline and storage networks

  • Work with front office to propose new trading strategies based on the logistics models

    1. Trade Signal Indicators
  • Develop online automated trade signal indicators that analyzes and forecasts future positions vs asset data and external market data

    1. Analytic Data Tools Enhancements
  • Continuously develop and improve trade tools and dashboards to facilitate speed on trading decisions

  • Partner with Digital Teams to transition data ingested into Power Platforms DataFlows to DataBricks.
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