AI/ML Expert · Data Scientist · Lecturer
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Dr. Forooz Shahbazi Avarvand

AI/ML expert with 10+ years of experience developing and deploying data-driven solutions across multiple domains, including natural language processing, industrial signal processing, and sensor-based systems.

Lecturer at HSLU Consultant Data Scientist at Xurce NLP & LLMs MLOps

Summary

AI/ML expert with 10+ years of experience developing and deploying data-driven solutions across multiple domains, including natural language processing, industrial signal processing, and sensor-based systems. Combines a strong academic foundation with extensive industry and consulting experience in pharma, tech, and manufacturing environments.

Specialized in transformer-based NLP and large language models, while also applying machine learning and statistical modeling to real-world engineering problems such as quality control, anomaly detection, predicitive maintenance and time-series analysis. Proven track record of delivering production-ready solutions—from scalable NLP APIs to real-time systems integrated into industrial pipelines—driving measurable business impact and operational efficiency.

Experienced in advising stakeholders on identifying high-value AI use cases, defining data strategies, and maximizing return on investment through practical and scalable implementations. Bridges academia and industry through roles as lecturer, module lead, and consultant, translating cutting-edge research into applied solutions while training and mentoring the next generation of AI professionals. Skilled in Python, cloud platforms, and modern MLOps practices. Strong communicator and mentor with professional fluency in English and German.

Work Experience

Data scientist consultant at Loepfe AG

2025—now
  • Improved reliability of production processes through designing and implementing signal processing and ML algorithms to automate quality control in textile sensor systems,
  • Rapidly acquired domain expertise in optical sensor physics to bridge knowledge gaps between data science and hardware systems, enabling accurate modeling and effective deployment of ML solutions in a previously unfamiliar technical domain
  • Collaborated with engineering and production stakeholders to translate operational requirements into robust, scalable solutions and support implementation in live environments
  • Optimized existing approaches and developed novel solutions for unresolved challenges under strict real-time and hardware constraints, enabling deployment directly on production machines
  • Advised on future ML opportunities by identifying advanced modeling approaches and defining data requirements, enabling the team to unlock additional value from new datasets and guide longer-term AI adoption

Module Lead & Lecturer at HSLU, Rotkreuz, Switzerland

2024–now
  • Module Lead and Lecturer in the MSc Program for MLOPs at Lucerne University of Applied Sciences and Arts, Lucerne, Switzerland. Feb 2026– now
  • Module Lead and Lecturer in the BSc Program for Data Engineering: March 2025– now
  • Identified a critical gap in the curriculum and initiated the introduction of a new Data Engineering module, aligning academic training with industry demands
  • Designed and delivered the module from the ground up, equipping students with practical skills in data pipelines, scalable systems, and modern data infrastructure on the cloud.
  • Module Lead & Lecturer in MSc for NLP: teaching transformers, semantic search, and LLM fine-tuning. 2024-now
  • Established and directed an international module in partnership with academia and industry in Toronto, aligning real-world project design with educational goals and leading full program execution across technical, scientific, and operational domains.
  • Supervised MSc and BSc theses in applied machine learning and NLP, including:
  • Enabling LLMs to cite their results and provide transparent outputs.
  • Developing and fine-tuning LLM solutions for legal applications.
  • Guest lecturer and external expert for NLP at HSLU, Switzerland. May-September 2024
  • Deputy head of AI and ML bachelor program at HSLU (ad interim). October 2024– August 2025, Feb 2026-July 2026

Senior Data Scientist at Bayer AG, Language AI, Berlin, Germany

2021–2025
  • Designed and deployed an end-to-end AI-driven platform for insight generation, enabling stakeholders to monitor product trends, evaluate post-launch risks, and make data-informed decisions at scale.
  • Led technical strategy for Generative AI initiatives through connecting the data science teams and the business stakeholders and translating the business needs to the technical language.
  • Mentored junior NLP engineers, improving team productivity and accelerating delivery of high-quality models through knowledge sharing and technical guidance
  • supervised a master thesis on fine-tuning large language models (LLMs) with in-house proprietary data at Bayer AG.
  • Deployed production-ready REST APIs for NLP inference using cloud infrastructure.

Research Scientist at Alexa AI, Amazon, Berlin, Germany

2019–2021
  • Collaborated with cross-functional teams to integrate NLP models at scale into Alexa, ensuring alignment with product requirements and seamless deployment.
  • Built and optimized NLU models for multi-task dialogue understanding.
  • Developed error analysis pipelines to identify misclassifications enabling targeted model improvements and increased robustness in production systems.

Senior Data Scientist at Siemens R&D, Digital Factory and Mobility, Germany

2017–2019
  • Reduced production costs and improved product quality by developing machine learning solutions for real-time detection of defects in sensor data, enabling automated quality control within manufacturing processes.
  • Created clear visualizations and reports to present results to engineers and management, supporting data-driven decision-making.
  • Patent holder: "Anomaly detection in track circuit devices using machine learning" - developed ML-based methods for automated detection of abnormal behavior in railway track circuits, reducing reliance on manual signal inspection.

Postdoctoral Researcher, Fraunhofer Heinrich-Hertz Institute (HHI), Berlin, Germany

2014–2017
  • Conducted laboratory EEG measurements and managed large-scale acquisition of multichannel sensor data.
  • Applied advanced signal processing and statistical modeling to study brain responses to 3D visual stimuli.
  • Developed and adapted Python scripts (numpy, scipy, pandas, statsmodels) for data cleaning, feature extraction, and visualization of results.
  • Documented and presented findings to cross-disciplinary research teams, strengthening skills in scientific communication and structured reporting.

Selected Personal Project with LLMs

Tiptoi-to-Farsi Translator (2025): Designed a fun personal project for my daughter using LLMs to translate Tiptoi pen content and books into Farsi, combining speech processing, NLP translation pipelines, and child-friendly interaction design.

Education

IT and Software Skills

Libraries and Frameworks: PyTorch, Huggingface, NLTK, transformers, gensim, Scikit-Learn, pandas, numpy, matplotlib, scipy, Keras, TensorFlow

Tools and Platforms: AWS services, Google Cloud, Docker, FAST API, Steamlit, PostgreSQL, Kubernetes, Git, Linux, Spark,

Programming Languages: Python, SQL, C, C++

Data Analytics: A/B Testing, Experiment Design

Personal Information

languages English (Fluent) , German (Fluent), Farsi (Native)

Awards

Let’s connect

Open to collaborations in AI, NLP, and applied machine learning.

Feel free to reach out for conversations around Generative AI, LLMs, production ML systems, AI education, or applied data science projects.

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