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 atwww.analog.com and onLinkedIn andTwitter (X).
Principal AI Engineer, Demand Forecasting
Lorenz Labs, ADI’s advanced AI engineering group within Edge AI, is pioneering the frontier of Physical Intelligence—developing foundation models and agentic systems that can reason about the physical world. As part of that mission, we're developing advanced forecasting models and agentic systems that drive high-stakes business decision-making. In this role, your aim will be to build the next generation of forecasting solutions that go beyond traditional analytics into cutting-edge time series foundation models.
Key Responsibilities
Lead the research and development of advanced demand forecasting models to drive business decision-making and operational efficiency.
Identify opportunities for improvement in existing forecasting solutions and implement innovative strategies to enhance accuracy and business impact.
Explore and implement cutting-edge time series forecasting techniques, including advanced deep learning models (e.g., DeepAR, MQRNN, N-BEATS) and time series foundation models (e.g., Chronos, TimesFM, TimeGPT).
Develop hierarchical forecasting approaches to address demand forecasting across multiple hierarchy levels and temporal granularities.
Drive innovation in forecasting algorithms to improve predictions for time series with sparse or limited historical data.
Enhance evaluation frameworks for forecasting models by proposing relevant metrics, conducting rigorous statistical tests, and quantifying real-world business impact.
Collaborate with cross-functional teams to integrate forecasting insights into broader business strategies.
Must-Have Skills
Expertise in time series modeling: Hands-on experience with training or fine-tuning foundation models or deep learning models on time series datasets.
Proficiency in Python programming: Strong knowledge of libraries such as PyTorch, TensorFlow, SKLearn, SKTime, Statsmodels etc.
Experience with statistical and machine learning models: ARIMA, ETS, Prophet, XGBoost, State Space Models, and other time series techniques.
Knowledge of intermittent time series forecasting: Familiarity with methods like Croston's method, Quantile Forecasting, and Hurdle Models.
Strong understanding of evaluation metrics: Expertise in time series evaluation metrics and statistical hypothesis testing.
Exceptional communication skills: Ability to effectively communicate complex forecasting results to stakeholders, gather feedback, and identify areas for improvement.
Decision-making under uncertainty: Capability to make informed modeling decisions in ambiguous scenarios and collaborate effectively within a team environment.
Preferred Education and Experience
Educational Background: MS or Ph.D. in Statistics, Mathematics, Econometrics, Operations Research, Computer Science, Electrical Engineering, or a related field.
Industry Experience: 10+ years of combined research and industrial experience in applying machine learning and/or deep learning models to solve demand forecasting or related problems.
Leadership Experience: Demonstrated ability to lead projects and teams in applying time series modeling to demand forecasting or similar domains.
Business Acumen: Proven track record of quantifying the business impact of forecasting models and aligning technical solutions with organizational objectives.
Familiarity with hierarchical and multi-granularity forecasting techniques.
Knowledge of forecast reconciliation techniques to align top-down and bottom-up forecasts.
Strong analytical mindset with the ability to translate technical insights into actionable business strategies.
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.
EEO is the Law: Notice of Applicant Rights Under the Law.
Job Req Type: ExperiencedRequired Travel: Yes, 10% of the time
Shift Type: 1st Shift/DaysThe expected wage range for a new hire into this position is $230,000 to $316,250.
Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.
This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.
This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.
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