Data Scientist I

Tulsa, OK, United States

Our E&P Approach

In every aspect of our operations, we strive to optimize capital efficiency, so we can develop more assets, provide more jobs and bring more energy to the world to positively impact more lives. We continually refine our portfolio of holdings, acquiring acreage with high oil cuts and divesting lower-margin assets. We seek to create efficiencies in our approaches to drilling, completions, crews, materials, transport, and all other facets of our business. In the end, Vital Energy produces something beyond oil and gas. We create value for our stakeholders, and for every human empowered by the energy we help to bring forth.

High productivity, every acre

Vital Energy acquires and develops oil and gas resources in the largest and most productive hydrocarbon region in the world, the Permian Basin. We focus on this thriving area because it best meets our goal to make energy plentiful and accessible to humanity, responsibly, over the long term. While our current holdings are fully within the Permian, our acquisition and development strategy considers all high-margin assets that can help sustain our business and fuel our purpose.

Better decisions through digital

Vital Energy embraces digital transformation like no other company in our space. We believe the potential for profound progress in our industry is limitless. This is our mindset. And it has spurred us to make several high-impact advancements. A few highlights include:

Dynamic Routing | Using AI algorithms, we optimally route lease operators to the highest value opportunities in the field.

Emissions Prevention | Computer vision and thermal cameras detect flaring and venting events, prompting fast remediation and prevention of further releases.

Optimal Chemical Usage | Water rates are fed to the cloud and IoT devices automatically adjust chemical injection rates.

ESP Well Optimization | AI algorithms automatically adjust back pressure, pump speed and other settings to maximize production and well life.

This is just the beginning. We see immense opportunities to harness the power of data to drive efficiency, improve decision-making, so we can produce more energy in better ways to sustainably power our planet.

Company: Vital Energy, a forward-focused digital upstream oil and gas enterprise.

About Vital Energy:

Based in Tulsa, OK, Vital Energy stands as a paragon of innovation within the upstream oil and gas sector. As a nexus between state-of-the-art technology and energy resource management, we have transformed the paradigm of operational efficacy through our innovative approaches. Not just a name, but a movement within the industry, Vital Energy epitomizes cutting-edge innovation, setting standards, and leading the charge with solutions that chart the future.

Why Choose Vital Energy? Innovation-Driven Impact: Vital Energy doesn't simply toe the line. We're at the forefront, ensuring that our operations reflect the latest in technological advances, propelling the industry into the future.

Acknowledged Excellence: With AI at the helm, our intricate adjustments to artificial lift and chemical pump settings, combined with the adept utilization of real-time field surveillance data, have crafted new benchmarks recognized widely across the sector.

Tangible Results: Our commitment to digital transformation is not mere rhetoric. We've actualized our aspirations, as illustrated by our significant upticks: a 2-3% increase in field production, 15% enhancement in gas lift run time, and a 4% rise in ESP run time.

Investor Confidence: Our technological strides aren't just internal milestones. They're central talking points during our investor interactions, reflecting the confidence and trust our stakeholders place in our vision.

Holistic Growth: Beyond mere operational achievements, our emphasis on change leadership and the integration of unique technologies fosters a culture ripe for continuous evolution and growth.

Role Description:

As an entry-level Data Scientist I at our oil and gas company, you will play a crucial role in supporting our data-driven decision-making processes. Your main responsibilities will include collecting, analyzing, and interpreting large complex datasets, developing predictive models and algorithms, and presenting insights to key stakeholders. You will collaborate with cross-functional teams to extract actionable information from vast amounts of structured and unstructured data, contributing to optimizing operational efficiency, identifying new business opportunities, and mitigating risks. By applying your expertise in statistical analysis, programming, and data visualization, you will contribute to improving our company's performance and advancing our technology-driven initiatives.

At Vital Energy, you will be more than just a Data Scientist. You'll be at the heart of a team shaping the future of the oil and gas industry. Step into our world in Tulsa, and together, let's revolutionize the energy landscape.

Technical Qualifications: Education: Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

Programming Skills: Proficiency in Python or R for data analysis and machine learning.

Machine Learning: Basic understanding of machine learning algorithms and statistical analysis techniques.

Data Manipulation: Proficiency in data manipulation libraries such as pandas and NumPy.

Problem-Solving: Strong problem-solving skills with attention to detail.

Communication: Excellent communication skills to convey complex technical concepts to non-technical stakeholders.

Team Collaboration: Ability to work collaboratively in a team-oriented environment.

Adaptability: Eagerness to learn and adapt to new challenges in a rapidly evolving field.

Big Data: Familiarity with big data technologies, especially within the AWS ecosystem.

Data Extraction: Experience with data extraction and transformation from unstructured sources.

Cloud Computing: Knowledge of cloud computing platforms, specifically AWS, including AWS Lambda, S3, Glue, and SageMaker.

Geospatial Data: Understanding of geospatial data analysis techniques.

Relevant Experience: Previous internships or project work in data science or analytics.

Key Responsibilities: Collect, clean, and preprocess data from various sources, including sensors, logs, and databases.

Build and implement machine learning models to predict and optimize key performance indicators related to oil and gas operations, such as production efficiency, equipment maintenance, and resource allocation.

Create clear and insightful data visualizations and dashboards to communicate findings and insights to non-technical stakeholders.

Collaborate with cross-functional teams, including engineers, geologists, and business analysts, to identify opportunities for data-driven improvements in operational processes.

Stay up-to-date with industry trends and advancements in data science and leverage this knowledge to drive innovation within the organization.

Maintain thorough documentation of data sources, methodologies, and model development to ensure transparency and reproducibility.

Actively seek opportunities to enhance the efficiency and effectiveness of data analysis processes.

COMPENSATION:

Salary is commensurate with experience.

WORKING CONDITIONS:

Work is normally performed in a climate-controlled environment, where exposure to conditions of extreme heat/cold, poor ventilation, fumes and gases is very limited. Noise level is moderate and includes sounds of a normal office environment. No environmental hazards are encountered in performance of normal job duties.

PHYSICAL DEMANDS:

Work normally requires finger dexterity and eye-hand coordination to operate computer keyboard at moderate skill level. Work may require occasional pushing, pulling, or carrying 20-pound objects such as files, documents, boxes, etc. Work involves sitting most of the time, but may involve standing and walking for brief periods. Travel is occasionally required.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)