Senior Data Scientist

Today’s world is crime-riddled. Criminals are everywhere, invisible, virtual, and sophisticated. Traditional ways to prevent and investigate crime and terror are no longer enough…

Technology is changing incredibly fast. The criminals know it, and they are taking advantage. We know it too.

For nearly 30 years, the incredible minds at Cognyte around the world have worked closely together and put their expertise to work, to keep up with constantly evolving technological and criminal trends and help make the world a safer place with leading investigative analytics software solutions.

We are defined by our dedication to doing good and this translates to business success, meaningful work friendships, a can-do attitude, and deep curiosity.

We, the cyber security group in Cognyte, are building a new and exciting next-gen Threat Hunting and Cyber Investigation platform. We use cutting-edge technologies to collect and combine unique data from various sources to allow the development of cyber oriented advanced analytics and swift investigation of advanced cyber-attacks.

The data science team greatly impacts the design of the cyber security product, the team develops ML models for detection of various cyber threats and attack scenarios.

We are looking for a highly skilled and motivated Senior Data Scientist to join our team. In this role, you will be responsible for developing innovative machine learning, NLP, and AI technologies, for solving problems within a wide scope.

As Data scientist you’ll make an impact on

Research and develop models for detection of cyberthreats.
Lead collaboration with our cyber experts research team, be able to develop all parts of the components for modelling (e.g., data collection, evaluation setting, model training, testing, and inference).
Working closely with the other development teams, architecture, product to create high quality deliverables.
Taking an active role in our agile processes, design reviews, brainstorming, and knowledge-sharing sessions.

Requirements:

For that mission you’ll need:

4+ years of production environment experience, working with predictive and probabilistic models, clustering algorithms, classification models - a must
MSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields - a must
Master PySpark and lead efforts to optimize distributed data processing pipelines for performance and scalability – a must.
Proven experience in bringing an ML algorithm from idea to productization.
Good applied statistics skills, such as distributions, statistical testing, regression, etc.
Team player, Ability to handle several tasks simultaneously.
Strong knowledge in Python, and NoSQL.
Relevant cyber experience – big advantage.

Our work model is hybrid, combining remote and on-site work. This allows us to get things done when and where we are most productive.

Career Page:
R&D