Senior Data Scientist

NOV Inc.•Houston, TX

2d•Hybrid

About The Position

As a Senior Data Scientist, you will partner with business leaders to identify high-value opportunities in areas such as demand planning, capacity/production planning, procurement, and financial forecasting. You will develop a firm understanding of specific business processes and real-world workflows, and work closely with cross-functional teams including domain experts, business analysts, data engineers, and software engineers. This role will lead data science initiatives that impact operations globally across multiple business units, defining project scope, timelines, and deliverables in collaboration with business leaders. You will architect scalable machine learning and forecasting solutions within cloud platforms such as AWS, Azure, Databricks, and Snowflake, ensuring models are production-ready, robust, and maintainable with appropriate monitoring and retraining pipelines. Additionally, you will develop standardized methodologies and frameworks to ensure scalability and consistency across diverse environments, and ensure compliance with data governance, privacy, and security standards while scaling analytics solutions globally. You will manage and mentor interns, junior data scientists, and analysts, and translate advanced analytics results into strategic recommendations for VP and C-level leadership. You will utilize programming languages such as SQL and Python for data manipulation, analysis, and model development.

Requirements

Master’s degree in a quantitative discipline
Five or more years of professional data science experience in manufacturing and/or supply chain environments
Hands-on experience working with ERP data and operational processes including order-to-cash, procure-to-pay, and demand-to-deliver
Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
Advanced proficiency in Python, SQL and PySpark; experience wrangling large relational datasets
Deep expertise in machine learning, forecasting and optimization
Experience deploying enterprise-scale solutions in cloud environments (AWS experience preferred)
Proficient in at least one data visualization library such as Matplotlib, Seaborn, or Plotly
Familiarity with MLOps practices, CI/CD pipelines, and model lifecycle management
Demonstrated ability to drive business impact and ROI through analytics
Strong track record of executive-level communication and influence
Experience leading cross-functional teams across multiple geographies

Nice To Haves

Knowledge of Streamlit for building interactive data applications preferred

Responsibilities

Partner with business leaders to identify high-value opportunities in areas such as demand planning, capacity/production planning, procurement, and financial forecasting
Develop a firm understanding of specific business processes and real-world workflows
Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers
Lead data science initiatives that impact operations globally across multiple business units
Define project scope, timelines and deliverables in collaboration with business leaders
Architect scalable machine learning and forecasting solutions within cloud platforms such as AWS, Azure, Databricks, and Snowflake
Ensure models are production-ready, robust, and maintainable with appropriate monitoring and retraining pipelines
Develop standardized methodologies and frameworks to ensure scalability and consistency across diverse environments
Ensure compliance with data governance, privacy, and security standards while scaling analytics solutions globally
Manage and mentor interns, junior data scientists and analysts
Translate advanced analytics results into strategic recommendations for VP and C-level leadership
Utilize programming languages such as SQL, Python for data manipulation, analysis and model development