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.
If you want to be part of a powerful team, we are looking for a skilled and motivated Applied Data Scientist to join our research group at Cognyte. As an Applied Data Scientist, you will work closely with our data engineers, research scientists, and software engineers to develop and implement advanced machine learning models and algorithms. You will play a key role in leveraging data-driven insights to enhance Cognyte's products and provide valuable solutions to our customers. This position offers an exciting opportunity to contribute to cutting-edge AI technologies in the fields of NLP, computer vision, pattern recognition, Large Language Models (LLM) and more.
As a Cognyter you will:
- Develop, implement, and optimize machine learning models and algorithms, including but not limited to LLM-related AI applications.
- Collaborate with data engineers to design and implement data processing pipelines for efficient model training and inference.
- Fine-tune pre-existing models and customize them to specific domains and customer requirements.
- Conduct experiments and analyze model outputs to evaluate their performance and identify areas for improvement.
- Stay up to date with the latest advancements in machine learning and AI research, and identify opportunities to leverage emerging techniques and technologies.
- Communicate and present technical findings, insights, and recommendations to both technical and non-technical stakeholders.
Your toolbox
- MSc or PhD degree in computer science, data science, or a related fields.
- 5+ years of relevant experience as a Data Scientist, applying machine learning techniques in practical projects.
- Solid understanding of machine learning algorithms and techniques, with hands-on experience in developing and implementing models.
- Proficiency in programming languages such as Python and experience with machine learning frameworks like TensorFlow or PyTorch.
- Familiarity with data preprocessing techniques, feature engineering, and model evaluation metrics.
- Strong collaboration skills with demonstrated ability to work effectively across teams.
- Strong problem-solving skills and the ability to apply analytical thinking to complex business problems.
- Strong attention to detail and the ability to work effectively in a fast-paced, collaborative environment.
- Willingness to travel abroad (10%).
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