לוח משרות דרושים Data Analyst מתאים גם לסטודנטים, לחיפוש זה נמצאו 2 משרות !

we are looking for a Clinical Data Labeler.
The Clinical Data Labeler contributes significantly to the training of our AI models, which aim to enhance the quality of life for senior citizens. This position involves meticulously tagging and classifying textual data based on clinical and technical criteria to ensure high-quality AI training datasets.
Key Responsibilities:
Review and analyze clinical textual data, including speech and other relevant sounds.
Accurately tag and classify textual data using clinical and technical criteria.
Collaborate with the AI team to refine and improve labeling guidelines.
Communicate regularly with the team to report challenges, suggest improvements, and ensure consistent data labeling.
Maintain a high level of attention to detail to ensure quality and accuracy in data labeling.

we are the agentic intelligence platform for cyber and quality teams. We protect and analyze data from millions of connected assets worldwide, including vehicles, robots, charging stations, fleets, and the broader physical-AI ecosystem - for Fortune 500 companies. Our platform spans AI and API security, cybersecurity XDR, proactive quality detection, and cyber threat intelligence.
we are looking for a highly motivated student to join our Data Analytics team. This role includes exploring and extracting insights from millions of connected vehicles on the road. As a Data Analyst, you'll develop the next generation of cybersecurity and mobility data applications for the automotive industry.
we are a fast-growing company and is looking for determined and devoted individuals. This is a chance to witness the connected vehicles revolution from a different angle. You will play a major role in the companys engagements, research large complex datasets, and use cutting-edge tools and methodology.
This role is part-time and is Israel based.
Responsibilities
Leading the data onboarding process of new customers.
Explore raw data of various customers as preparation for parsing and normalization in order to turn data into actionable insights and make data-driven decisions.
Use big data tools and AI to analyze large scale real-time data of connected vehicles and identify anomalies and emerging threats to create meaningful detectors that bring value to our customers.
Representing the data function both internally and externally, including customer-facing interactions.