Lead Data Scientist

Onesubsea; Houston (TX); Hybrid; USD 120,000 - 180,000; Full time

Job summary

SLB seeks a senior data science leader to design and deploy production-grade AI, ML, and PHM solutions for oilfield assets. You will build end-to-end data pipelines, time-series analytics, and model governance across Dataiku, Azure, and GCP, with edge/near-edge deployments when required.

You will mentor teams, create dashboards and interfaces using React or Dash, implement ModelOps, and ensure reliable performance in asset-intensive environments such as ESP systems.

Qualifications

• Master’s degree in Data Science, CS, or related STEM field with 3+ years of experience in data science roles.
• Experience deploying ML/AI/PHM solutions in industrial settings using time-series data.

Responsibilities

• Provide technical leadership for end-to-end analytics and AI system development.
• Lead data pipeline design, model development, validation, deployment, and monitoring.
• Develop and deploy LLM-based workflows and AI-enabled applications for stakeholders.
• Mentor data science teams and contribute to architectural decisions and governance.

Skills

Time-series analysis

PHM analytics

ModelOps

LLM integration

Edge deployment

Mentoring

Prognostics

Dashboard design

Education

Master's degree

Tools

Dataiku

Azure

GCP

React

Dash

Job description

Responsible for providing technical leadership in the design, development, deployment, and lifecycle management of advanced data science, machine learning, and artificial intelligence solutions for industrial and production engineering applications. Focus on building scalable, production-grade analytical systems that support predictive maintenance, operational optimization, and engineering decision-making for asset-intensive environments, including pumps and electric submersible pump (ESP) systems. Design and implement end-to-end data science workflows encompassing data ingestion, feature engineering, model development, validation, deployment, monitoring, and continuous improvement. Require hands‑on development of prognostics and health management (PHM) models using time‑series, event‑based, and operational datasets, as well as the implementation of ModelOps practices to ensure model reliability, version control, performance tracking, retraining, and governance in production environments. Lead the development and deployment of AI‑enabled applications, including web‑based analytical tools, dashboards, and decision‑support systems, to deliver insights to technical and business stakeholders. Architect, build, and operate production‑grade large language model (LLM) agents and LLM‑based workflows, integrating them with enterprise data sources, analytical models, and software systems, and ensuring these solutions meet scalability, performance, and operational requirements. Leverage enterprise data science platforms, such as Dataiku or equivalent tools, to orchestrate analytics pipelines, manage model lifecycles, and enable collaboration across teams. Provide technical guidance and mentorship to other data scientists, contribute to architectural decisions for analytics and AI systems (including edge or near‑edge deployments where applicable), and ensure compliance with internal software development, data governance, security, and operational standards.

Master’s degree in Data Science, Computer Science, Computer and Information Science, Statistics, Engineering, Applied Mathematics, or a related STEM field, or foreign equivalent, plus 3 years of post‑baccalaureate experience in the job offered or in data scientist, machine learning engineer, applied AI engineer, or related analytical job titles.

Applicants must have 3 years of experience in the following:

• (1) Applying domain knowledge of oil and gas equipment and production systems to develop or deploy machine learning solutions using operational and sensor data for PHM, condition monitoring, or production optimization in production environments;
• (2) reliability analytics using operational, sensor, and event‑based data;
• (3) deploying and operating machine learning models in production systems, including integration and execution for edge or near‑edge applications;
• (4) integrating machine learning, deep learning, LLM‑based systems, and visualization tools with production engineering workflows;
• (5) machine learning and deep learning model development for industrial assets, including predictive maintenance, anomaly detection, forecasting, and asset health monitoring in oil and gas production and engineering environments;
• (6) enterprise data science and cloud platforms, including Dataiku, Microsoft Azure, and Google Cloud Platform (GCP), to build and manage data pipelines, ML workflows, and GenAI applications;
• (7) Generative AI and RAG systems, including deploying and operating architectures combining LLMs with structured and unstructured data sources;
• (8) building interactive dashboards and analytical interfaces using frameworks such as React, Angular, Dash, or Streamlit.

Telecommuting permitted less than 50% per week within the same geographic location as the assigned Schlumberger Office location.

ALL APPLICANTS FOR U.S. ROLES MUST CAREFULLY READ ALL THE SUPPLEMENTAL U.S. SPECIFIC INFORMATION LISTED BELOW.

SLB is committed to a culture where everyone feels like they belong. To learn more about our diversity, equity, and inclusion commitments, please visit our Diversity & Inclusion | SLB (slb.com) page for more information.

When certifying your application, you are also certifying on reading and understanding all of the below supplemental information. For purposes of the application and the below information, Company shall be defined to mean SLB. Please note that the below supplemental information and the employment application are NOT a contract.

1. EQUAL EMPLOYMENT OPPORTUNITY & VETERANS

Company policy is to provide every individual a fair and equal opportunity to seek employment and advancement at the Company without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, citizenship, genetic information, veteran or military status, disability, creed, ancestry, pregnancy (including pregnancy, childbirth and related medical conditions), marital status or any factors protected by federal, state, or local laws. We are an "Equal Opportunity Employer". For more information please, refer to the latest version of "Know Your Rights" poster and the "Pay Transparency Nondiscrimination Poster" located here: https://www.dol.gov/agencies/ofccp/posters. The Company is a VEVRAA Federal Contractor - priority referral Protected Veterans requested.

2. REASONABLE ACCOMMODATIONS

The Company will endeavor to make a reasonable accommodation / modification to the known physical or mental limitations of a qualified applicant with a disability to assist in the hiring process, unless the accommodation would impose an undue hardship on the operation of our business, in accordance with applicable federal, state, and local law. If you believe you require such assistance to complete the application or to participate in the interview process, please contact [e-mail] to request assistance.

Please note that only those inquiries concerning a request for reasonable accommodation will be responded to.

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Pursuant to the Immigration Reform and Control Act of 1986, all applicants who are offered and accept employment must produce documents establishing their identity and authorization for employment in the United States. These documents must be produced no later than seventy‑two (72) hours after employment commences. In addition, all applicants who are offered and accept employment will be required to verify their employment authorization under oath by signing a USCIS Form I-9. SLB is an E-Verify employer.

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5. STATE INFORMATION

Please read below any applicable State Information. By certifying the application, you are also certifying that you have read and understood any applicable State Information that is listed below.

• ARIZONA APPLICANTS ONLY: To the extent required by applicable law, the Company maintains a smoke‑free workplace.
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• MASSACHUSETTS APPLICANTS ONLY: Note that it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
• MARYLAND APPLICANTS ONLY: Under Maryland law, an employer may not require or demand, as a condition of employment or prospective employment, that an individual submit to or take a lie detector test. An employer who violates this law is guilty of a misdemeanor and subject to a fine not exceeding $100.
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