We’re on the lookout for a Senior Data Scientist who has great social skills, initiative, and integrity. Ideal candidates will have exceptional business judgment and quantitative analytic ability. Our Senior Data Scientist will play a key part of the Deanta strategy and will work closely with our proprietary project management and content editing system called Lanstad.
Job responsibilities include:
- Apply advanced data science, AI and machine learning techniques to solve challenging real-world problems in the areas of system performance and linguistic programming.
- Engage in on-going learning to identify and develop valuable new sources of data and machine learning technologies with applicability to Deanta’s product and solution roadmap.
- Work with customer-facing platforms and teams to understand and meet the needs of Deanta’s clients and end-users.
- Collaborate with product development teams and contribute to product design, development, delivery and support.
- Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
- Utilise statistical natural language processing to mine unstructured data, and create insights; analyse and model structured data using advanced statistical methods and implement algorithms and software needed to perform analyses.
- Build document clustering, topic analysis, topic modelling, text classification, named entity recognition, sentiment analysis, and part-of-speech tagging methods for unstructured and semi- structured data.
- Perform elements of data cleaning, feature selection and feature engineering and organise experiments in conjunction with best practices.
- Creating dynamic decision making processes and trying to predict future events from the historical data.
- Benchmark, apply, and test algorithms against success metrics.
- Interpret the results in terms of relating those metrics to the business process.
- Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
- Visualise data to tell compelling stories.
- Leading the planning and implementation of data science projects.
- Coordinating project staff.