Clément Sicard

🇫🇷 data professional living in 🇨🇭, with international experience in {🇺🇸,🇨🇭,🇫🇷,🇸🇪}

Lausanne, Switzerland

CS

About

With a background in theoretical machine learning and experience in Big Data and software engineering, I strive in both AI/ML and Data Engineering roles. I have worked for 5+ years on a wide range of technical projects in a variety of different fields: giga-scale battery manufacturing, academic research, consulting, environmental services, financial services, startups and international organisations. I aim to leverage my experience to help companies build and deploy data products, while having a positive impact on society, especially on social justice and climate change mitigation. My research interests focus on deep learning and its applications to multimodal data for action recognition tasks, with a stress on audio.

Work Experience

New York University
New York, 🇺🇸

09.2023 - Now

Deep Learning Research @ Music & Audio Research Lab (MARL)

Research on online multimodal audio-visual scene understanding with neuro-symbolic learning • Focus on off-scene events in egocentric videos using visual and audio transformers. Tech stack: Python, PyTorch, HPC

United Nations
New York, 🇺🇸
Remote

03.2023 - 09.2023

NLP Research

Semantic analysis then named entity recognition on all sorts of documents from UN Digital Library • Search engine as a network visualization, linking docs by refined topics, member state, cross-references… Tech stack: Python, Hugging Face, PyTorch, TypeScript, React.js, Sigma.js, Neo4j, Docker

Northvolt
Stockholm, 🇸🇪
Remote

07.2022 - 09.2023

Data Science/Engineering Consultant

ELT data ingestion pipelines on AWS stack (Lambda, Redshift, RDS, Kinesis, Firehose, DynamoDB, S3) • Data modelling in SQL for a fully-automated battery manufacturing gigafactory Tech stack: Python, AWS Cloud Stack, Golang, SQL, dbt, Streamlit, Pandas, Looker, Kubernetes, Docker, Scala

swissQuant Group
Zurich, 🇨🇭

12.2020 - Now

Quant Engineer (Software & Maintenance)

Supporting maintenance of a risk engine software • Contributed to a financial risk engine and developed an engine performance monitoring dashboard for daily reports • Tech stack: Python, Bazel, Vue.js, Pandas, Plotly, Java, Jenkins, GCP Cloud Stack, Kubernetes

Green PRAXIS
Marseille, 🇫🇷
Remote

04.2020 - 07.2022

Lead Engineer (Software & Data)

Worked on crawling, cleaning and ingestion of geographical data to feed a statistical biodiversity model • Developed a cross-platform app and model to support our biology experts team with ML recommendations. Tech stack: Dart, Python, TypeScript, IBM Cloud Stack, MongoDB, Redis, Plotly, Flutter, QGIS, GeoPandas

Research Assistant @ Digital & Cognitive Musicology Lab (DCML)

Contributed to the ms3 Python library, part of PyPi to convert several music sheet formats into XML • Contributed to a corpora of classical pieces, performing analysis and classification on music metadata. Tech stack: Python, SQL, BeautifulSoup, Pandas, Selenium

Education

ETH Zurich

2021 - 2024
MSc. in Computer Science. Focus on AI/ML theory & research. Core courses incl. Deep and Reinforcement Learning, Probabilistic AI, Big Data, XAI, Social Data Science

New York University

2021 - 2024
MSc. Thesis @ Music & Audio Research Lab (MARL) under the supervision of Prof. Juan P. Bello

Ecole Polytechnique Fédérale de Lausanne

2017 - 2021
BSc. in Communication Systems. Core Courses incl. Calculus, Algebra, Signal Processing, Object-Oriented Programming, Probabilities, Statistics

Skills

Python
Data Engineering
Deep Learning
Software Engineering
PyTorch
Machine Learning
SQL
Big Data
dbt
Scala
Spark
AWS
Pandas
Golang
Docker
Flutter
Dart