Gather and clean large volumes of structured and unstructured data from various sources. Apply statistical, machine learning and traditional and generative AI techniques to analyse data, identify patterns, and develop predictive models. Create visual representations of data to communicate insights and findings to non-technical stakeholders. Interpret data analysis results to provide actionable insights and recommendations for business decisions. Work closely with cross-functional teams to understand business needs, develop solutions, and implement data-driven strategies. Stay updated with the latest trends and advancements in data science, machine learning, and related technologies to improve methodologies and processes. Ensure compliance with data privacy regulations and ethical standards in handling sensitive information. What you'll bring:
Previous applied experience within a data science role. Demonstratable knowledge of extracting business value from data science using both quantitative and qualitative metrics. Strong mathematical and statistical background. An ability to understand and translate data into actionable insights for the business. Strong working knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow and PySpark. Good understanding of industry standard MLOps capabilities. Understanding of the financial industry, in particular insurance, would be advantageous. If you're excited about the prospect of using data to make a meaningful difference in people's lives, we want to hear from you!
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