Mandatory : Python, Azure Data Pipelines, SQL Experience- 5+ years of relevant experience. Notice Period- Immediate to Max 15 Days Detailed R&R as below:
Designing, building, and deploying compute environments and data pipelines to serve analytics models
Utilising the latest available technologies to flexibly manage and scale data pipelines and analytics models
Engineering complex systems to manage big data compute tasks
Challenging and collaborating to derive new and novel techniques to improve the service of data to models
Developing platforms and processes that support the reproducibility of results
Ensure best in class processes and techniques to develop and deploy data analytics solutions to the business
Ensure the quality assurance and quality control of all data analytics products released to the business
Capture and record the intellectual property generated.
Share what has been developed in GitHub to help foster a new generation of data driven decision makers and enable them to improve upon what has already been done
Engage with clients and key stakeholders to build their understanding of data analytics
Provide training and knowledge transfer to support the deployment and continuity of the analytics products developed
To succeed in this role, you should have:
Postgraduate qualification in Mathematics, Statistics, Computer Science or related field combined with several years of experience in data science projects, preferably using agile methodologies
Pipeline development, across different data architectures, (transactional, time series, streaming, unstructured) and storage solutions including use of APIs
Cloud based solution design using containerisation and severless architectures in AWS and/or Azure (Cloud Formation/ARM)
Implementation of data science projects, including familiarity with machine learning libraries, and frameworks (e.g. Sci-kit Learn, H2O, TensorFlow, Keras, Tidyverse) x
Coding in SQL, Python, Linux (Bash), Scala and Go (desirable); software engineering experience desirable
Massive parallel processing architectures, inclusive of the use Hadoop and/or Spark (desirable)
Engage with clients and key stakeholders (IST) to build their understanding of data analytics
Drive change by fostering an innovative and \xe2\x80\x9cdisruptive\xe2\x80\x9d technology culture to identify and drive value creating opportunities
Help the broader PACE team and clients prioritize by advising technical complexity of identified opportunities
EY is committed to being an inclusive employer and we are happy to consider flexible working arrangements. We strive to achieve the right balance for our people, enabling us to deliver excellent client service whilst allowing you to build your career without sacrificing your personal priorities. While our client-facing professionals can be required to travel regularly, and at times be based at client sites, our flexible working arrangements can help you to achieve a lifestyle balance. About EY As a global leader in assurance, tax, transaction and advisory services, we\xe2\x80\x99re using the finance products, expertise and systems we\xe2\x80\x99ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we\xe2\x80\x99ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.
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