Join Our Winning Team at INEOS Energy

Company: INEOS Energy

Are you looking to be a part of a winning team where employees are empowered to make a difference? INEOS Energy is seeking talented individuals like you.

Who We Are

INEOS Energy is the energy division of INEOS. We specialize in producing and trading oil, gas, power, liquefied natural gas (LNG), and carbon credits. Our operations span across the Danish and UK North Sea with offshore oil & gas assets, and onshore assets in South Texas, US. We are supported by significant investments and projects in low carbon technologies, helping us transition towards sustainable energy solutions.

Our US Onshore Business

Our key focus in the US Onshore business is the acquisition, exploration, and development of properties to efficiently and safely produce natural gas, oil, and NGL from underground reservoirs. Our primary assets are located in the Eagle Ford shale basin in South Texas, generating over 36kBOE per day from 2,000 wells.

Owning and operating producing US onshore assets aligns with INEOS Energy’s strategy to build a global integrated portfolio, offering high-quality energy solutions and supporting the energy transition.

About the Position

Job Title: Data Scientist- Operations

Department: Operations

Summary of Position

We are seeking a Data Scientist to collaborate with field operations and engineering teams to identify and address daily inefficiencies. The primary goal is to create data-driven solutions that enhance user capabilities, automate workflows, and allow teams to tackle higher-level challenges. The Sr. Data Scientist will use their technical expertise to develop solutions closely tied to revenue generation.

Key Responsibilities

• Partner with field operations and engineering teams to understand and address daily challenges and inefficiencies.
• Develop data-driven solutions to automate workflows and enhance user capabilities.
• Utilize machine learning, statistical modeling, and data analysis techniques to drive operational improvements.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Implement and maintain data pipelines, machine learning models, and real-time monitoring systems.
• Create visualizations, dashboards, and reporting tools to effectively communicate insights.
• Continuously explore and evaluate emerging technologies to enhance operational efficiency.

Qualifications

• 4-year degree in Computer Science, Computer Information Systems, Management Information Systems, or related field.
• At least 5 years of experience in an upstream organization providing solutions to internal clients.
• Strong foundation in statistics, mathematics, and machine learning algorithms.
• Proficiency in programming languages such as Python, R, and SQL.
• Experience with machine learning frameworks like scikit-learn, TensorFlow, PyTorch, or Keras.
• Knowledge of time series analysis and anomaly detection techniques for SCADA data.

Relocation:

Preferential treatment will be given to candidates residing in the Denver metropolitan area.

Work Authorization:

INEOS USA Oil & Gas LLC is not currently sponsoring employment visas for this position.

Compensation & Benefits

Compensation:

The annual rate for this position ranges between $163,000 - $200,000. This role offers an opportunity for a company-wide annual discretionary bonus of up to 30% of eligible pay. Depending on skills and experience, participation in the Long-Term Incentive Plan with annual awards vesting over three years, ranging from 8-15% of stated annual target, may be available. Compensation is estimated based on a successful Colorado applicant and may vary for positions outside of Colorado.

Benefits:

Our benefits package includes healthcare, dental, and vision insurance for employees and eligible dependents. INEOS also offers several wellness, financial, and work/lifestyle-specific benefits. Our 401(k) retirement plan includes a 3% company contribution and a match of up to an additional 6% of eligible compensation. We offer generous paid time off including sick and