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BP Americas, Inc. Data Scientist in Denver, Colorado


Job title:

Data Scientist



Req ID:


Relocation available:


Travel required:

Yes - up to 25%

About BP:

BP's BPX Energy business (formerly known as the Lower 48) operates across a vast US geography, from Texas north through the Rocky Mountains. The business manages a diverse portfolio which includes an extensive unconventional resource base of about 7.5 billion barrels of oil equivalent across 5.5 million gross acres in some of the largest and most well-known basins in the US. Headquartered in Denver (Colorado), BPX Energy employs about 1,700 people across six states, operates more than 9,600 producing wells and has 70,000 royalty owners. Our vision is to be the premier, high return, onshore exploration and production company that consistently increases asset value. Our Wyoming operations are anchored on the giant Wamsutter tight gas field in the south central part of the state. In the San Juan area of Colorado and New Mexico we produce from tight gas sands and operate the largest coal-bed methane field in the US. Our Mid-Continent operations cover the prolific Anadarko, and is home to the famed East Texas basin, along with the Woodford shale gas play and Arkoma basin. We also have non-operating interests in over 10,000 wells across the US with substantial positions in both the Eagle Ford and Fayetteville shale basins. In 2018, BP completed a $10.5 billion acquisition of BHP's world-class unconventional oil and gas assets in the Permian-Delaware basin in Texas, along with two premium positions in the Eagle Ford and Haynesville basins in Texas and Louisiana. These assets currently produce 190,000 barrels of oil equivalent per day, of which about 45 percent are liquid hydrocarbons. The deal represents BP’s largest purchase since buying ARCO in 1999. It is a transformational acquisition for our BPX Energy business which gives the BPX Energy team access to some of the best acreage in some of the best basins in the onshore U.S.

Job Family Group:

Research & Technology Group

Job Profile Summary:

The Data Scientist will be intricately involved in running analytical experiments in a methodical manner, and will regularly evaluate alternate models via theoretical approaches.The role will participate in the team’s engagement with business stakeholders and partners to enhance the existing analytics solutions and develop new solutions to business problems.The role requires a thought leader that will be instrumental in providing inputs to the Data Science & Analytics Team for the design and building of predictive models and algorithms, exploratory data analysis, test design, statistical tests and measures, and business value measurement.

Time Type:

Full time


United States of America


United States - Colorado - Denver

Job advert:

Key accountabilities

  • Evolve skills, solutions and the organization to predictive & prescriptive analytics

  • Reporting and visualizations development to develop storytelling – using any of SSRS, Spotfire, PowerBI, realtime dashboarding, MI/BI and shallow analytics best practices.

  • Deliver quality analytic solutions, combining science with the software development process and challenging current data science trends with new ideas and alternative methods

  • Design and implement data analysis, data mining, research, analysis, and modeling strategies and best practices to internal clients

  • Ownership of the development and delivery of data science solutions from concept to production

  • Manages research targeted for innovations to solve business needs and technical challenges

  • Serve as the subject matter expert to articulate areas such as strategic, business and data analytics & statistics, data science, big data, normalization and modeling

  • Initiates data science based solutioning with a focus on revenue growth and achievement of the business’ overall targets and objectives.

  • Responsible for the preparation of documentation, presentations, and scientific based papers to communicate ideas to business leaders and executives.

  • Personally, works on challenging fundamental data science issues where necessary, realizes, and develops solutions independently.

  • In conjunction with Data Engineers, building and managing new data tables that support data collection, cross-functional data integration, data visualization, dashboards, predictive analytics, and data mining.

  • Leverages data science tools and techniques in analyzing large data-sets that will enable development of custom models and algorithms to uncover insights, trends, and patterns in the data, which will be useful in availing informed courses of action.

  • Create data science platforms to test and experiment with techniques inclusive of advanced analytics, behavioral modeling, and churn capitalizing on new data science approaches that can yield revenue for the business.

  • Responsible for the evaluation of analytics and machine learning technologies in use in the business and communicates findings to key stakeholders through reports and presentations.

  • Partners with other non-technical departments within the business assisting them in understanding how data science can benefit them and improve their effectiveness and performance.

  • In collaboration with Data Engineers, Data Architects and Data Management, works closely with the IT department within the business for the purpose of facilitating easy and effective access to computing and data resources within the business.

  • Takes initiative and stays up to date with the latest data science trends, techniques, and best practices, determining how to incorporate the most suitable practices in the department.

  • Collaborative role with interaction with non-technical departments and, as such, will need to have exceptional communication skills in order to be able to tailor and convey technical messages in a clear and understandable manner, leading to business-wide improvement of data management, informed decision making, and ultimate improvement in performance.

  • Enhancing data collection procedures to include information that is relevant for building analytic system

Essential Education

  • A degree (Master’s or PhD preferred) in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.

Essential experience and job requirements

  • 3+ years of hands on experience in machine learning (supervised, unsupervised and ensemble methods), natural language processing or computer vision. Deep learning experience is a bonus

  • Proven track record of developing, scaling and implementing these models in customer facing environments

  • Strong programming skills: R, Python, Java etc along with stellar visualization and persuasive story telling

  • Knowledge and exposure to cloud technologies, Azure and/or AWS.