About Analog Devices

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).

          

Senior Principal Data Scientist, Demand Forecasting

Analog Devices

Overview
Analog Devices builds the technology that enables breakthroughs at the Intelligent Edge. Our products are deeply embedded in our customers’ systems and are often designed in years before they reach production. As a result, our supply chain plays a critical role in delivering on customer commitments while balancing long manufacturing lead times, complex product portfolios, and highly variable demand signals.

Demand forecasting is a foundational capability that ensures the right products are built at the right time, in the right quantities, to support customer success and business growth. Accurate forecasts directly impact customer service levels, inventory health, factory utilization, and financial performance. As a Principal Data Scientist focused on demand forecasting, you will play a central role in advancing how ADI predicts demand, translates uncertainty into decisions, and operationalizes advanced analytics at scale across the supply chain.

Role Description

We are seeking a Principal Data Scientist to lead the development, deployment, and continuous improvement of demand forecasting models for a complex, global semiconductor supply chain. This role sits at the intersection of data science, supply chain, and product delivery, with a strong emphasis on practical impact, production readiness, and decision support.

You will work closely with supply chain planners, operations leaders, data engineers, and software teams to translate business questions into robust modeling approaches and ensure solutions are deployed reliably into production systems. This role requires both technical depth and the ability to influence across functions.

Key Responsibilities

• Design and build advanced demand forecasting models that operate across multiple horizons, aggregation levels, and product hierarchies
• Apply probabilistic and statistical approaches to model uncertainty, bias, and forecast error in a way that supports downstream decision making
• Develop models using classical machine learning techniques such as regression, classification, time series modeling, hierarchical forecasting, and Bayesian methods
• Incorporate external signals, business context, and domain knowledge into modeling approaches rather than relying solely on historical patterns
• Partner with data engineering and platform teams to deploy models into production, monitor performance, and support ongoing retraining and improvements
• Evaluate and experiment with newer AI and machine learning techniques, including deep learning, transformers, and foundation model approaches, where they add measurable value
• Establish best practices for model validation, backtesting, interpretability, and performance monitoring in a production environment
• Communicate results, tradeoffs, and uncertainty clearly to technical and non-technical stakeholders, including senior leadership
• Mentor and provide technical leadership to other data scientists, setting standards for modeling quality and rigor

Required Qualifications and Experience

• Deep, hands-on experience building demand forecasting or related predictive models for real-world, operational use cases
• Strong foundation in probability, statistics, and applied mathematics, with demonstrated ability to reason about uncertainty and bias
• Expertise in classical machine learning methods, including regression, classification, and time series techniques
• Practical experience deploying models to production, including working with imperfect data, system constraints, and operational requirements
• Proficiency in Python and common data science and machine learning libraries
• Experience working cross-functionally with business, engineering, and operations partners
• Ability to translate complex modeling concepts into actionable insights for decision makers

Preferred Qualifications

• PhD or Master’s degree in a quantitative discipline such as mathematics, computer science, economics, physics, statistics, or a related field
• Experience in supply chain, demand planning, manufacturing, or industrial forecasting environments
• Familiarity with modern AI and machine learning trends, including deep learning architectures, transformers, and foundation models, with a pragmatic view on when and how to apply them
• Experience with cloud-based data and machine learning platforms
• Track record of leading technically complex projects from concept through production

Why Analog Devices
At Analog Devices, you will work on problems that matter at global scale, influencing how critical technologies reach customers across industries. This role offers the opportunity to shape core forecasting capabilities, apply rigorous data science to high-impact decisions, and help define the future of analytics in a complex manufacturing environment.

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For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export  licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls.  As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.

Job Req Type: Experienced

          

Required Travel: Yes, 10% of the time

          

Shift Type: 1st Shift/Days