Data Scientist

You may not realize it, but you’ve likely used a product today made possible by the plastics and chemicals manufactured by Chevron Phillips Chemical. From medical supplies and electronics to food packaging and cosmetics, we create the building blocks for more than 70,000 consumer and industrial products.

 

Even as a global company with 5,000 employees, we maintain a “small company feel” and uphold a culture of respect, diversity, and inclusion. Ask any Chevron Phillips Chemical employee what they like best about their job, and universally, the answer is “the people I work with!” We value work-life balance, and love to see our employees thrive both professionally and personally. There has never been a better time to work for Chevron Phillips Chemical. If you’re ready to grow with us and become part of our vision of being the premier Chemical Company, apply today!

 

Purpose/Introduction

We are seeking a Data Scientist to join our dynamic team in developing and deploying advanced analytics projects within an agile environment. This role offers an excellent opportunity for a professional with a strong background in data science to apply their skills to real-world business challenges across manufacturing and petrochemical industries. You will collaborate with different business units, data engineering, and analytics teams to identify and execute machine learning opportunities. You will work with diverse datasets from multiple sources — including commercial, financial, and manufacturing — and of various types including structured, semi-structured, unstructured, and time-series data.
 

This role is eligible for hybrid and 9/80 work schedules. 

Responsibilities

• Analyze and perform Exploratory Data Analysis (EDA) on raw datasets
• Develop visualizations to present key findings from EDA
• Identify potential machine learning opportunities that drive business value
• Cleanse and prepare data for machine learning model development
• Engineer features to enhance model performance
• Perform hypothesis testing to assess the feasibility of machine learning applications
• Plan and execute model lifecycle management using MLOps best practices
• Apply statistical and machine learning techniques to uncover insights and solve complex problems
• Collaborate with cross-functional teams to integrate models into business processes and decision-making
• Utilize time series analysis techniques on relevant datasets
• Keep up to date with developments in data science, including Generative AI

Responsibilities (continued)

⦁    Leads technical projects with understanding of project management methodologies
⦁    Adheres to change management and other IT internal controls
 

Required Qualifications

• Bachelor’s degree in a quantitative field engineering, computer science, mathematics, statistics, or data science. Higher degree preferred. (High School Diploma/GED and 2 years of experience in a data science position may be considered in lieu of a formal degree)

Preferred Qualifications

• Proven ability to apply advanced analytics techniques to real-world problems
• Strong understanding of statistical analysis and machine learning methods
• Proficiency in Python, with at least a working knowledge of SQL
• Experience with time series analysis is a huge plus
• Interest or experience in Generative AI is advantageous
• Strong written and verbal communication skills
• Ability to work effectively in a team environment; familiarity with Agile methodologies is beneficial
• Curiosity and enthusiasm for learning new domains
• Experience with big data platforms such as Spark is advantageous; experience with Databricks is a bonus
• Experience with MLOps tools, such as MLflow, is a plus
• Familiarity with cloud platforms such as Microsoft Azure, AWS, or GCP is highly beneficial
• Experience with reinforcement learning is a plus

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