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Job Summary
This role will be responsible for the application of data engineering methods, which include data engineering, analytics, data architecting, big data, machine learning, deep learning, artificial intelligence, predictive analytics to meet the companyâ€s business interests as well as that of our esteemed clients. In this role, you will assist in the development of data platforms and product development, to identify key business questions through data collection and using a wide range of statistical, machine learning and applied mathematical techniques to deliver insights to decisionmakers.  Job Responsibilities Support the CTO/lead data scientist using a variety of state-of-the-art open-source and cloud-based technologies to solve data analysis and prediction problems. Perform and build extract, transform and load data (ETL) products originating from diverse sources. Identify and act on new opportunities for data-driven business in data science and analytics. Recognize when existing solutions can be generalized to solve new problems. Work in a collaborative environment developing data science methods, tools and solving problems. Become fluent in analytical modelling using various modelling platforms. Work on newest tools and technologies to achieve results. Pre-process and transform data for model building and analysis. Troubleshoot data quality issues and work with team members to reach solutions. Perform descriptive analytics to discover trends and patterns in data. Create visualizations, including dashboards to provide insights on large data sets and input to finished reports. Analyze output products to assure data quality and conformance to requirements. Participate in continuous improvement efforts to increase available data quality and speed of delivery. 5-7 years of data analysis experience. Any relevant degree. Certifications or accreditations in AWS cloud technologies, foundational, cloud practitioner through to associate, architect and specialist level. Certifications or accreditations in data tools. Exposure to data visualization tools such as Power BI or Amazon QuickSight.  Skills: Ability to develop, build and model ETL tools that are fit for purpose. Ability to visualize data using various tools. Ability to manage time and project deliverables. Ability to communicate with stakeholders and clients. Ability to work in an ever-changing, unstructured environment. Ability to work as part of a team, with vastly differing skill sets and opinions. The ability to contribute ideas to the quorum.
Planet10
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