The Data Analyst I
is responsible for developing data-driven operational tools, and supporting data-systems, to improve performance within the business unit. Successful candidates must be able to collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems, including, but not limited to; understanding the operational process, developing paths for data gathering (when required), and using statistical methods to optimize performance. Key accountabilities
- Research, develop, and implement methods for measuring and analyzing production performance
- Utilize business intelligence software, such as Spotfire, to development data-analysis tools that drive business decisions
- Work directly with optimization engineer(s), facility engineer(s), production engineer(s), field leadership, IT, and analysts in order to understand and continuously evaluate the organization's workflow, using data to identify optimization opportunities
- Work as part of geographically dispersed team, effectively communicating prioritized business unit needs and prioritized project statuses, while providing assistance and training to other team members
Essential experience and job requirements
- Minimum requirement of four-year college degree
- Advanced degree and/or training in computer science, data science, operations research, applied mathematics, or statistics (preferred)
Other Requirements (e.g. Travel, Location)
- Proven proficiency in basic SQL to include joining, grouping, and table creation
- Demonstrated ability to apply statistical or data mining techniques to solve real problems
- Demonstrated ability to constantly learn outside of a classroom environment, and successfully apply learnings
- Demonstrated self-motivator
Yes - up to 50% travelDesirable criteria & qualifications
- 0-3 year of relevant work experience, including experience with database querying and statistical data analysis such as linear models and multivariate analysis
- Proficiency in an object-oriented programming language
- Experience using technology to work efficiently with datasets such as MATLAB, Python, or R
- Ability to draw conclusions from data and recommend actions
- Ability to succeed in a fast-paced environment, deliver high quality performance on multiple, simultaneous strategic, value-added tasks and priorities
- Relentless drive, determination, and self-learning ability
- Highly organized and attentive to detail
- Demonstrated willingness to both teach others and learn new techniques
Yes - Domestic (In country) onlyTravel required
Yes - up to 50%Is this a part time position?
BP's US Lower 48 (L48) Onshore business 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 Houston (Texas), L48 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 most respected and admired oil and gas company in the Lower 48 US states.
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 2015, the L48 Onshore is being established as a separate business within BP's Upstream to manage its onshore oil and gas assets across the US onshore. This effort is being undertaken to improve competitiveness and help L48 remain at the forefront of innovation and development of technologies for unconventional resources.
[ "01-Mar-2017" ]
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