Our Favorite CITGO Perks are:

• Remote Work options available for eligible positions • Options are department and/or location specific • 9/80 Work Schedule Option (where applicable) • Annual Vacation Incentive (40-120 hours of additional pay) for Eligible Employees • Paid Vacation Time • Company-Paid Holidays • Parental Leave • Excellent 401(k) Match • Pension Plan • Company-Paid Sick Leave and Long-Term Disability • Medical, Dental, & Vision Plans; FSA and HSA options • Company-Paid Life Insurance for Active Employees • Healthy Rewards Program • Service Awards Program • Educational Assistance Plan • Dependent Children Scholarships • Reimbursement for Gym Membership • Employee Discount Programs • On-site Health Clinic • On-site Cafeteria (select locations) • On-site Credit Union and ATM (Corporate office only) • On-site Fitness Center (select locations) PLEASE NOTE ALL JOBS DO NOT QUALIFY FOR ALL PERKS

Relocation

Relocation Benefits are not available for this position.

Note

Employer will sponsor visas for position

Job Summary

Work with Commercial Analytics Research & Development team to establish data science capabilities within CITGO. Design, develop and implement data-driven solutions that help the organization make better decisions, and drive the adoption of data-driven decision making within the organization. The role requires a combination of technical skills in data science, software engineering and machine learning, as well as communication and project management skills.

Analysis is concerned with three primary areas: (1) Optimization Solutions, such as measurement of competitive performance and its drivers, customer/product mix, sales lift studies, price elasticities, etc., (2) Predictive & Exploratory Analytics, such as demand forecasting, prioritization of trends, market potential for new business models, (3) Thought Leadership, such as applying augmented decision making with ML/AI, creative use of internal and external data sources with pragmatic curiosity.

Individual will act as an individual contributor within a group of technical personnel.

Identify business areas where data science approaches can enrich decision making & implement appropriate solutions.

Individual will function in the capacity of a full stack decision scientist to address majority of initial hard data science needs as data science team begins establishment.

Individual will develop and implement predictive modelling to optimize profitability and decision-making capabilities.

Individual will collaborate with stakeholders to understand business needs and decision-making processes.

Requires very strong understanding of the business drivers of decision making and communicating complex insights to a diverse audience.

Requires application of well-developed technical knowledge in data science, conducting and coordinating difficult, responsible assignments.

Requires comfortability taking the lead on data science efforts for identifying, justying & implementing advanced analytics efforts.

Minimum Qualifications

Degree:

• Bachelor’s Degree.

• Masters degree or higher in computer science, statistics, data science or similar strongly preferred

The minimun number of years of job related experience required by this job is:

• 7-10 years.

List any specialized training or unique skills required:

• Deep understanding of data science/decision science concepts and techniques, as well as hands on experience building data-driven solutions using machine learning algorithms, statistical models and data visualization tools, required.
• Experience with major cloud computing platforms (Azure, AWS, etc.) required.
• Experience with Azure platforms strongly preferred.
• Proficiency in data analytics tools such as Python, R, SQL preferred.
• Comfortability with taking initiative & having an entrepreneurial spirit is strongly preferred.
• Understanding of downstream oil & gas business preferred.
• Ability to effectively manage project timelines, budgets and resources is necessary.
• Excellent written and verbal communication skills preferred.
• Strong knowledge of data privacy, security and governance regulations/best practices.
• Ability to simplify complex information.
• Desire and willingness to continuously expand knowledge and skills.
• Passionate and creative about solving complex and difficult problems, both in group and individual settings
• Applicant must be self-starter and comfortable with situations where solutions are not always clear or obvious.

Job Duties

Develop & implement data-driven solutions to support decision making, such as predictive models, data visualization dashboards and machine learning algorithms. Communicate the results of data science projects to key stakeholders and executive leadership, promoting the adoption and integration of data science into decision-making processes.

Collaborate with Commercial Analytics R&D & business units to identify and prioritize data science projects that can deliver business value. This may involve conducting data analysis and data discovery activities to understand the current state of the data assets and how they can be leveraged to support decision making.

Collaborate with Commercial Analytics R&D team to establish the necessary strategies, technical infrastructure and tools to support data science activities, including data storage, data processing and machine learning. Approaches for this should have a heightened focus on approaches that are innovative, organizationally sustainable, modern, transparent and efficient.

Ensure that data privacy, security and governance standards are met in all data science projects. Work with IT and Commercial Analytics R&D to implement appropriate measures for data collection, processing, storage and protection. Ensure that data is of high quality, properly documented, and stored and managed in a manner that meets regulatory and organizational requirements.

Stay current on new techniques, technologies and tools in data science, machine learning and the oil and gas industry and evaluate and determine their potential applications for the organization. Requires a commitment to ongoing professional development and a willingness to continuously expand expertise, which includes attending regular training, industry events, reading trade publications and engaging with colleagues and peers in the field.