DBS Data Scientist

About the Role

As a Data Scientist (Drilling Analytics) at NOV Downhole Broadband Solutions you will transform real-time and historical drilling data into actionable insights that improve operational performance efficiency and decision-making. Working closely with engineering operations software development and customer teams you will ensure data quality develop analytical frameworks and deliver meaningful reporting and visualization solutions.

This role combines data science advanced analytics and operational domain expertise to support drilling optimization initiatives and drive value from high-density downhole data. You will play a key role in improving how drilling data is managed contextualized analyzed and utilized across the organization and by our customers.

About the Company

NOV Downhole Broadband Solutions specializes in drilling automation and optimization through advanced real-time downhole data technologies. Leveraging Wired Drill Pipe (WDP) and Along-String Measurement (ASM) solutions we provide high-density low-latency data that enables smarter safer and more efficient drilling operations.

Our technologies help customers improve drilling performance reduce operational risk and unlock greater value from their data through innovative digital solutions and advanced analytics.

What We Offer

At NOV you will have the opportunity to apply data science in a highly practical operational environment where your work directly impacts drilling performance and customer outcomes.

We offer:

• The opportunity to work with unique real-time and historical drilling datasets
• Exposure to cutting-edge drilling automation and digital technologies
• Collaboration with multidisciplinary teams across engineering software operations and data science
• Opportunities to contribute to innovative analytics and digital product development
• A supportive environment that encourages continuous learning and professional growth
• Access to modern analytical tools and AI-enabled technologies
• The ability to make a measurable impact on operational efficiency and customer success
• A global organization with opportunities for long-term career development
  

Core Responsibilities

• Manage clean structure and contextualize drilling and operational datasets from multiple internal and customer systems.
• Ensure data quality consistency integrity and traceability across analytics and reporting workflows.
• Apply advanced statistical techniques to identify trends anomalies operational risks and improvement opportunities.
• Support drilling performance analysis post-operation reviews and optimization initiatives through data-driven insights.
• Develop dashboards reports and analytical products for both internal stakeholders and customers.
• Collaborate with engineering operations and software teams to improve data workflows digital solutions and analytical capabilities.
• Support the development of data models contextual frameworks and scalable analytics solutions for drilling data environments.

Additional Responsibilities

• Contribute to data pipeline improvements and analytical product development initiatives.
• Evaluate and leverage AI-enabled tools to improve productivity analysis documentation and workflow automation.
• Support continuous improvement efforts related to drilling data management and operational intelligence.
  

Qualifications & Skills

Essential Qualifications

• Bachelors or Masters degree in Data Science Statistics Mathematics Engineering Computer Science Physics or a related technical field.
• Experience working with complex technical or operational datasets preferably within drilling energy industrial manufacturing or other operational environments.
• Strong knowledge of:
  • Data management
  • Data contextualization
  • Data quality control
  • Statistical analysis and advanced analytical methods
• Ability to communicate analytical findings effectively to both technical and non-technical stakeholders.
• Fluent English communication skills both written and verbal.

Desired Qualifications

• Experience utilizing AI-powered tools to enhance software development data analysis documentation and workflow automation such as GitHub Copilot Claude Code Claude for Enterprise or similar technologies.
• Experience with dashboard development data pipeline design and analytical product development.
• Knowledge of R or other statistical programming languages.
• Understanding of drilling operations well operations or oilfield data environments.
• Familiarity with operational data management and contextualization within industrial or energy-related settings.
• Technical Skills - proficiency in:
• Python
• SQL
• Power BI
• Spotfire
• Microsoft Excel
• Industry Systems Experience -Experience with one or more of the following systems would be advantageous:
• OpenWells
• ProNova
• Wellcom
• NOV Max Platform
• Max Data Services
• WellData
• Electronic Drilling Recorder (EDR) systems
• Drilling Beliefs & Analytics (DBA)
• Rig Cadence
• WELS
• Kabal
  

Soft Skills

We are looking for someone who demonstrates:

• Strong analytical and critical thinking skills
• Curiosity and a continuous improvement mindset
• Excellent attention to detail and commitment to data quality
• Strong collaboration and stakeholder management skills
• Ability to work effectively across multidisciplinary teams
• Strong problem-solving and decision-making capabilities
• Ability to translate complex data into practical business insights
  

Why Join Us

At NOV data is at the heart of innovation in drilling performance and operational excellence. As a Data Scientist (Drilling Analytics) you will work with industry-leading technologies and unique datasets that directly influence drilling operations around the world.

You will join a team that combines engineering expertise operational knowledge and advanced analytics to solve real-world challenges. This is an opportunity to make a tangible impact expand your technical capabilities and contribute to the future of digital drilling solutions while building a rewarding career within a global technology leader.

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