Houston, Texas, United States
Houston, Texas, United States
Skills: IT - Analysis & Management, IT - Software Development
Experience: 7 + Years
Education: Bachelors/3-5 yr Degree
Employment Type: Full Time Salaried Employee
Location: Houston, Texas, United States
We are looking for the right people - people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world's largest providers of products and services to the global energy industry.
As a data scientist and machine learning software engineer on Halliburton Digital Solution team, you are responsible to deliver digital solutions which can achieve measurable business results through collaborating with subject matter experts in businesses, applying common open source libraries for building data analytics models, prototyping data driven digital tools to tackle business problems. We are looking for top talents who enjoy learning and contributing to our team through creative and innovative thinking.
- Efficiently extract large scale complex business data (time series data, structured/unstructured) from various data sources and prepare them for data analytics.
- Partner with product experts, leverage common open source Machine Learning/Deep Learning packages for identifying data patterns/trends or building predictive models.
- Deploy solutions to business units using software technologies to generate measurable values for businesses.
- Grasp the application of the latest machine learning & artificial intelligence open source packages, cloud and distributed computing technologies to ensure the best technologies are implemented to meet businesses' data challenges.
- Undergraduate degree in Data Science, Computer Science, or Math, or Statistics.
- For candidates who hold an engineering degree, we require candidates have taken data science classes already.
- 7 years of experiences with a minimum of 2 years experiences in extracting the data, using common classification or regression open source packages through R or Python.
- Has basic knowledge with big data platforms like Hadoop, Hive, or Phoenix, as well as knowledge in parallel programming, and distributed computing frameworks like Spark.
- Advanced degree in in Data Science, Math, Statistics, Computer Science, or Engineering:
- 5 years of experiences with a Master's degree.
- 2 years of experiences with a PhD degree.
- Has experience with open source machine learning packages and deep learning packages provided by Microsoft Azure, Amazon AWS, or Google GCP (such as Scikit-learn, Azure ML, TensorFlow, Sagemaker).
Potential candidates are required to pass a data challenge test before on-site interview can be scheduled.
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
3000 N. Sam Houston Parkway E., Houston, Texas, 77032, United States
Requisition Number: 87825
Experience Level: Experienced Hire
Job Family: Engineering/Science/Technology
Product Service Line: Global R&D
Full Time / Part Time: Full Time
Additional Locations for this position:
Compensation is competitive and commensurate with experience.
Founded in 1919, Halliburton is one of the world’s leading providers of products and services to the upstream energy industry.
Halliburton is proud to be a services company, and our customers and investors appreciate our business model. Our strong competitive position not only comes from our geographic footprint and wide range of products and services, but also, more importantly, from the quality of our work and the dedication of our employees.
With approximately 55,000 employees, representing 140 nationalities in more than 80 countries, Halliburton touches much of the oil and gas that fuel our society.
Halliburton comprises 14 product service lines (PSLs). The PSLs operate in two divisions: Drilling and Evaluation, and Completion and Production.
Our Consulting and Project Management PSL works across both divisions and is the spearhead of our integrated-services strategy. Its financial results are included in the Drilling and Evaluation Division. PSLs are primarily responsible and accountable for strategy, technology development, process development, people development and capital allocation.
Integrity: Ethics and integrity are the foundation of our brand and the guiding principles for all we do.
Safety: Priority number one. We are focused on our own personal safety, as well as on the safety of others.
Collaboration: We work together with customers, and understand that everyone has a role in providing the best solution.
Competition: We compete to win, knowing that competition makes everyone stronger.
Creativity: We are resourceful. We are innovative, and strive to apply the right technology and solution every time.
Reliability: We deliver what we promise. We believe the quality of our service defines who we are.
Respect: We are honest with ourselves and with each other. We value our diverse skills and talents, and know we are stronger together as one family.
These values are our corporate DNA, the foundation for how we relate to each other and to every individual and entity with whom we interact. These are the principles that every Halliburton employee is expected to use, live by, and demonstrate on a daily basis.
Own Your Career
Our people are essential to our ability to innovate, achieve, grow, and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. We invest in our employees through leadership and competency development, competitive compensation plans, health benefits, work-life programs, and reward and incentive plans.
Opportunities for career development – and the tools you need to take advantage of them – are abundant. Combine those opportunities with your drive and capabilities, and your career path can go in nearly any direction you choose.