Is innovation part of your DNA? Do you want to enable a connected future for people, organizations, and society?
Join our growing global NTT team and you’ll be part of the world’s largest ICT company (by revenue). We’ve combined the capabilities of 28 remarkable companies to become one, leading technology services provider. Together, we help our people, clients, and communities do great things with technology to create a more secure and connected future. We employ 40,000 people across 57 countries. By bringing together the world’s best technology companies and emerging innovators, we work together to deliver sustainable outcomes to businesses and the world. Innovation is part of our DNA. We believe it’s key to what makes us different. So, we strive to move forward, challenge the status quo, and drive excellence through the technologies we integrate and the services we deliver around the world. The result is connected cities, connected factories, connected healthcare, connected agriculture, connected conservation, connected mobility, and connected sport. Together we enable the connected future.
Want to be part of the team?
As a problem solver, you will design, manage, deliver and implement complex data and information management platforms in areas such as business intelligence, machine learning, data mining, complex data analytics, taking a solution from strategy through implementation to managed service.
You will work in some of the most challenging and exciting domains across government and industry, grappling with the most interesting and varied data sets Australia has to offer. You will be undertaking complex research in the application of data governance, data analytics and science techniques to industry business problems along with designing data management and analytics processes and models to to deliver insights and meet business outcomes
Your day at NTT:
- Designing, architecting, and implementing complex batch and real-time data analysis solutions and services in business intelligence, predictive and prescriptive analytics, data science, data management, and information management, utilising Agile (Scrum) frameworks
- Designing, developing and implementing data collection, transformation, and data integration solution, machine learning algorithms and scripts to create, coordinate and deploy information and analytics solutions, pipelines and data storage
- Developing reporting and data analytics solutions, tools and APIs
- Publishing and enforcing Big Data Analytics Tools best practices, configuration recommendations
- Providing technical guidance as SME and hands on delivery team member across multiple clients and engagements
- Contribute to thought leadership, and demonstrate personal excellence in the business application of advanced analytics techniques
- Building relationships with clients and identifying opportunities for data design improvement
- Managing multiple client engagements and potentially leading several teams
Key Skills Required:
- Proven experience producing artefacts, prototypes, process models, and dealing with complex data sets, data platform/techniques and analytics solutions
- Knowledge and experience developing queries and/or custom analytical processing in R or python for ad hoc requests and projects, as well as ongoing reporting.
- Proven experience Experience designing across multiple big data technologies, such as MS Azure, GCP, AWS, Cloudera, Marklogic, Neo4j, Splunk, Cassandra, Spark, Kafka, etc.
- Expertise designing, developing and implementing robust production-grade systems for data ETL, SQL for reporting and data transformation, developing integrations for data ingestion, data mapping and data processing capabilities (large scale ETL, BI and/or Analytical platforms)
- Experience designing data mining and analytics solutions with a range of software and statistical development platforms (such as R, Python, etc).
- Excellent understanding of a range of predictive and descriptive modelling techniques
- knowledge in popular techniques and algorithms for predictive and descriptive modelling techniques, data mining and machine learning.