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NOV

Senior Data Scientist

NOV

. Partner with business leaders to identify high-value opportunities, understand workflows, define requirements, and select analytical approaches across sales, manufacturing, supply chain, and finance .

Posted 11/6/2026full-timeHouston • Texas • United StatesSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in developing and deploying machine learning models and AI applications, with a strong focus on data governance and collaboration across business units. Proven ability to communicate complex findings to diverse audiences and mentor junior team members.

Highest-signal resume keywords
Machine Learning Model DevelopmentAdvanced SQL SkillsPython ProgrammingMLOps ExperienceCloud Solutions Deployment (AWS/Azure)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data ScienceFeature EngineeringStatistical ModelingDeep LearningModel OptimizationData PreparationValidationExperiment TrackingVersion ControlDistributed Processing (PySpark)
Soft Skills
Strong Communication SkillsMentoringInfluencing Stakeholders
Tools & Technologies
DatabricksSnowflakeAWSAzure
Certifications & Qualifications
Master's Degree in Quantitative DisciplinePhD in Quantitative Discipline
Industry Keywords
SalesManufacturing OperationsSupply ChainERP SystemsFinance

Tech Stack

Tools & technologies
AWSAzureCloudERPPySparkPythonSnowflakeSQL

About the role

Key responsibilities & impact
  • Partner with business leaders to identify high-value opportunities, understand workflows, define requirements, and select analytical approaches across sales, manufacturing, supply chain, and finance
  • Collaborate with domain experts, business analysts, data engineers, software engineers, and integration teams
  • Lead cross-business-unit and global data science initiatives, defining project scope, timelines, and deliverables with business leaders
  • Develop and validate machine learning models from data preparation and feature engineering through algorithm selection and optimization
  • Deploy and maintain production-ready models and AI applications, including evaluation, monitoring, alerting, versioning, and retraining
  • Design and evaluate agentic AI solutions, including tool-using workflows and retrieval-augmented generation when appropriate
  • Establish reusable analytical and engineering practices for scalable, reliable solutions
  • Apply data governance, privacy, and security standards
  • Mentor interns, junior data scientists, and analysts
  • Communicate findings and actionable recommendations through clear visualizations to technical, business, and executive audiences

Requirements

What you’ll need
  • Degree in a quantitative discipline such as Computer Science, Engineering, Statistics, or Mathematics, or equivalent experience
  • 3 to 5 years of data science experience, including delivering high-impact projects from problem definition through production and demonstrating business results; equivalent experience considered
  • Strong communication skills, including explaining technical work and influencing executive stakeholders
  • Advanced SQL and Python skills
  • Applied machine learning expertise in supervised and unsupervised learning, deep learning, feature engineering, statistical modeling, validation, and optimization, with evaluation against business outcomes
  • Experience deploying and supporting enterprise-scale data science or AI solutions in AWS or Azure cloud environments
  • Working knowledge of MLOps and software engineering, including version control, testing, CI/CD, experiment tracking, model versioning, deployment, and monitoring
  • Knowledge of sales, manufacturing operations, supply chain, ERP systems, or finance is a plus
  • Experience with Databricks or Snowflake; both is a plus
  • Strong PySpark skills for distributed processing
  • Practical knowledge of agentic AI, including tool/function calling, retrieval-augmented generation, orchestration, guardrails, observability, and evaluation; ownership of at least one solution from architecture through deployment or operations
  • Master’s or PhD in quantitative discipline preferred