Data Scientist

Wiliot was founded by the team that invented one of the technologies at the heart of 5G. Their next vision was to develop an IoT sticker, a computing element that can power itself by harvesting radio frequency energy, bringing connectivity and intelligence to everyday products and packaging, things previously disconnect from the IoT. This revolutionary mixture of cloud and semiconductor technology is being used by some of the world’s largest consumer, retail, food and pharmaceutical companies to change the way we make, distribute, sell, use and recycle products.

Our investors include Softbank, Amazon, Alibaba, Verizon, NTT DoCoMo, Qualcomm and PepsiCo.

We are looking for a data scientist with proven hands-on skills to join the team and build high-performing, scalable applications that turn time-series telemetry into data products. You will collaborate with great people from multiple disciplines to create innovative digital products and integrate them within the Sensing-as-a-Service cloud platform.

Requirements:

BSc in Computer Science or Electrical Engineering or equivalent. Higher degree is an advantage.
Strong background in statistics
Experience with Data science and ML
Experience with AI/DL/TS models is an advantage
At least 3 years of development experience in Python
Experience with cloud data environments and big data ETL procedures, cloud architecture (AWS/GCP/Azure)
Experience with IOT an advantage
Familiarity with some ML/data-processing frameworks and libraries (TensorFlow, Keras, PyTorch, JAX, Spark, Scikit-learn, Pandas) is an advantage
High self-learning and independent working abilities
Strong spoken and written English
Strong interpersonal and communication skills

#LI-Hybrid

Responsibilities:

Rapidly experiment and build models to clean signals and provide valuable insights to our customers.
Implement algorithms and SW solutions, considering large scale, high availability, security, robustness, performance, and cloud aspects.
Work hands-on with the data using SQL, PySpark, and other tools to extract, analyze, and visualize data.
Understand and oversee all phases of the development life cycle, such as Automation, CI\CD, TDD, Integrations, Builds, and Deployment.
Work with cross-functional stakeholders such as product management, marketing (can delete), and SW engineering.
Make strategic recommendations on data collection, integration, and retention requirements incorporating business best practices.