Senior Data Scientist

Job summary

Lead the design and deployment of scalable machine learning and forecasting solutions to optimize global operations in manufacturing and supply chain. Partner with business leaders to translate advanced analytics into strategic recommendations for C-level leadership.

Job details

Reports to: VP Data & Analytics 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 * 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 SUGGESTED QUALIFICATIONS * 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 * Knowledge of Streamlit for building interactive data applications preferred * 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 Please note that this is a hybrid position and requires candidates to work onsite in our Houston office three days per week. All interviews will be held in person.

What you’ll do

Lead the design and deployment of scalable machine learning and forecasting solutions to optimize global operations in manufacturing and supply chain. Partner with business leaders to translate advanced analytics into strategic recommendations for C-level leadership.

Requirements

Requires a Master's degree in a quantitative discipline and at least five years of professional data science experience in manufacturing or supply chain environments. Must be proficient in Python, SQL, and cloud platforms with a proven track record of deploying enterprise-scale solutions.

Listed skills

• Microsoft Azure · Preferred
• Data visualization · Preferred
• SQL · Preferred
• CI/CD · Preferred
• Machine learning · Preferred
• Amazon Web Services · Preferred
• Python · Preferred
• Forecasting · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• SQL
• PySpark
• Machine Learning
• Forecasting
• Optimization
• AWS
• Azure
• Databricks
• Snowflake
• MLOps
• Data Visualization
• Streamlit
• CI/CD
• Supply Chain Analytics
• Executive Communication

Job areas

• Data & Analytics
• Technology
• Manufacturing
• Logistics
• Engineering

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