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we are looking for a MXDR Analyst to join the team of cybersecurity analysts monitoring services 24/7, tiers 1-2. The role includes development of detection analyses, triage of alerts, investigation of security incidents, proactive threat hunting and enhancement of sensors and overall visibility status. The suitable candidate should be a team player with previous experience in SOC, SecOps or security monitoring, independent, and with a can-do attitude.
Responsibilities:
Working across all areas of SOC, including continuous monitoring and analysis, threat hunting, security compliance, security event auditing and analysis, rule development and tuning, and forensics.
Solving security incidents in accordance with defined service level agreements and objectives.
Prioritizing and differentiating between potential incidents and false alarms.
Addressing clients enquiries via phone, email, and live chat.
Working side-by-side with customers, providing insightful incident reports.
Working closely with peers and higher-tier analysts to ensure that your analysis work meets quality standards.
Identifying opportunities for improvement and automation within the MXDR Operation Lead, and leading efforts to operationalize ideas.
Identifying and offering solutions to gaps in current capabilities, visibility, and security posture.
Correlating information from disparate sources to develop novel detection methods.

As a Senior Data Scientist, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models in the domains of dating, moderation and content segmentation and apply them to tasks such as recommendation systems and analytics at a high scale.

Responsibilities:
Work with management and partner teams to design and implement solutions in recommender systems for given objectives.
Lead technical efforts to improve the performance of deep learning models and propose initiatives to impact company goals directly.
Autonomously find solutions to complex problems in social network recommendations and understand the data generation process and challenges with the data.
Analyze and leverage the extensive data received from our application to enhance model performance and accuracy.

We're looking for an applied deep learning researcher with strong and proven capabilities of building and deploying deep learning algorithms in the computer vision domain.
The AI team is building deep neural networks and computer vision algorithms for our smart-cart solution. Including identification of which product was inserted into the cart from a set of up to hundreds of thousands of different products in stores around the world.
The team includes Algorithm researchers and Data operations who together build a scalable training-pipeline, capable of training on millions of images for multiple tasks.
About The Role:
Own the full development cycle from researching a problem, defining the required dataset, implementing an efficient model, deploying it to production, and improving it upon real-world results.
You will work on computer-vision problems such as object detection, fine-grained classification, computational geometry, localization, tracking, and more.
Use, adapt and improve state-of-the-art implementations and adjust them to various project needs.

As a Senior Big Data Engineer on our BI team, youll build and scale the data infrastructure that powers our business insights. Youll design and implement robust data pipelines to process billions of daily records, leveraging cutting-edge cloud technologies and visualization platforms to transform data into actionable intelligence.

If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!

Responsibilities:
Design, Build, and operate scalable infrastructure for optimal data extraction, transformation, and loading from a wide variety of data sources, utilizing SQL, cloud migration tools, and Big Data technologies.
Work with a variety of programming languages, systems, frameworks, and cloud technologies, including Python, DBT, Airflow, AWS, Linux, Spark, and more.
Collaborate with customers and internal stakeholders to resolve data-related technical issues and support their data infrastructure and business needs.
Implement data validation, monitoring, and governance practices to ensure data accuracy, consistency, and security.

Responsibilities:
Design and develop application security software.
Research and implement new product features.
Come up with innovative solutions for hard to solve problems.