Apply📍 Ireland, Spain, Portugal, Greece, United Kingdom
🧭 Full-Time
🔍 Cybersecurity
🏢 Company: BforeAI
- You have a Master's or Ph.D. in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.
- You have proven industry experience of at least 4 to 5 years in data science, particularly with a focus on cybersecurity or networking.
- You have a solid understanding of cybersecurity principles, threat detection, and network protocols.
- You have strong programming skills in Python.
- You have experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn.
- You are proficient in data manipulation and analysis using SQL.
- You are proficient in working with NoSQL databases like MongoDB, Redis, Neo4j.
- Preference for experience with Vector databases.
- You are familiar with big data technologies such as Spark, Flink, and Kafka.
- You are familiar with workflow orchestration frameworks like Airflow and Kubeflow.
- You are familiar with distributed search and analytics engine like Elasticsearch.
- You have experience with data visualization tools such as Tableau, Power BI, or similar.
- You have hands-on experience with Microsoft Azure and Azure AI platform; experience with AWS or GCP is a plus.
- You must have experience with MLOps (i.e., deploying, monitoring, and maintaining machine learning models in production environments).
- Develop and implement advanced machine learning models and algorithms to detect and respond to cybersecurity threats and anomalies in network traffic.
- Analyze large, complex datasets from various sources to identify patterns, trends, and insights related to cybersecurity and network performance.
- Collaborate with cybersecurity analysts, network engineers, and other stakeholders to understand their requirements and translate them into technical solutions.
- Design and conduct experiments to evaluate the effectiveness of different algorithms and models detecting security threats to optimize performance.
- Build and maintain scalable data pipelines and architectures to process and analyze real-time and batch data.
- Create and deliver clear, concise, and actionable reports and visualizations for both technical and non-technical stakeholders.
- Lead with innovation and stay at the forefront of data science, cybersecurity, and networking advancements, continuously bringing new ideas and methodologies to the table.
- Mentor and guide junior data scientists, providing technical leadership and fostering a culture of continuous learning and improvement.
PythonSQLElasticSearchKafkaMachine LearningMicrosoft AzureMongoDBPyTorchRedisNosqlSparkTensorflow
Posted 11 days ago
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