The data scientist will contribute to the company’s development by collaborating with product managers, developers, and analysts to create an AI-ML framework for Scout’s value-added services.
Responsibilities include (but are not limited to):
- Work with enormous datasets and use sophisticated analytical approaches to complex challenges.
- Conduct end-to-end analyses, from data collection through analysis, reporting, and presentations.
- Develop a thorough grasp of Scout data structures, algorithms, and metrics.
- Use AI/ML/DL approaches to tackle supervised and unsupervised learning challenges.
- Build and prototype analytic pipelines iteratively.
- Create use cases, test scenarios, and test execution for all analytics features prior to product release.
The ideal data scientist will be capable of resolving difficult unstructured challenges via data-driven analysis and will have a strong dedication to growing the business’s income.
Key Requirements and Qualifications:
- Master’s degree in Computer Science or Mathematics preferable.
- Expertise in processing large amounts of structured and unstructured data, utilising data science approaches to deliver substantial business impact.
- This includes Deep Learning, statistical modelling and machine learning. It also includes econometrics and graph theory.
- A solid understanding of statistical and deep learning models.
- Coding, Algorithms, and High-Performance Computing.
- Excellent writing and spoken communication abilities, especially the ability to simplify complicated issues/scenarios.
For those who think they are competent in just a few of these areas, don’t worry! Individuals with a growth attitude and shown learning aptitude can apply.
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If you are interested in this opportunity, send an email to email@example.com.