דרושים » מדעים מדוייקים » Quantitative data Scientist בחברה בתחום ה-Algo Trading

We seek a strong, motivated, and highly technical researcher who can be part of the Innovation & Research team.

With an R&D mindset, the research outcome will be integrated into products.

The position allows gaining extensive knowledge about security-related issues based on Machine Learning algorithms that would help to secure organizational networks, including IoT devices.

You will be able to directly impact protections against major vulnerabilities.

Key Responsibilities
Be part of the Innovation team that is responsible for Policy Insights and IoT security solutions.
Build ML/AI solutions together with a strong partnership with our engineering team.
Work with data throughout the entire pipeline from Data Engineering and Data Analytics to ML/AI models.
Collaborate with all the data & research-related groups within .
Developing and implementing protection mechanisms against diverse cyberattacks, while investigating IoT devices to analyze their network behaviours and integration within complex systems.
Productization & development of technologies from the POC stage into an enterprise-scale security solution.
Work closely with other development teams, QA, product management, and customers.

Our Algorithms team tackles the companys most pressing ML challenges, addressing real-world problems that have a direct impact on success. As part of this group of experienced, you will help establish a new research area within the company, uncovering insights and detecting anomalies that enhance the products overall performance.



What You'll Do:

End-to-end ownership: Identify and frame ambiguous business problems, set measurable success criteria, prototype solutions, and deliver production-ready algorithms.
Algorithm design: Develop and refine methods across clustering, graph learning, causal inference, time-series modeling, and optimization to enable new product capabilities.
Workflow deep dive: Work closely with Product teams to analyze current pipelines, map data and decision flows, and identify inefficiencies and opportunities for improvement.
Real-world data modeling: Explore, structure, and model construction-related data, including progress histories and schedules. Build robust datasets and meaningful features.
Collaborate with a dynamic team of talented researchers driving digital transformation in the construction industry.

Data-driven insights. Help identify new products and opportunities for the company in diverse domains.
Develop Machine Learning models. Define requirements & combine data from a wide set of sources to develop ML/DL models that will automate and speed up our business processes.
End to end model management. Conduct in depth research, POC, write production-grade code and implement it (all the way to production) using our MLOps Infra to solve a diversity of business problems