The Covid-19 pandemic is creating seismic challenges around the world. Our purpose, to build a better working world, has never been more important. Life at EY has been transformed dramatically but our strong culture of flexible and remote working has helped EY people navigate new ways of working and remain connected with each other and our clients.
A better working world truly starts with the people at EY who are building it every day. Now more than ever we need talented people from diverse backgrounds to help our clients navigate the complexities of this Transformative Age: people with the passion, curiosity and drive to make things better.
We are seeking a Data Scientist to join our Data and Analytics team. This role is offered on a flexible, full-time basis.
EY DnA is the data and advanced analytics capability within EY Asia-Pacific, with over 500 specialist employees working across multiple industry sectors.
We implement information-driven strategies and systems that help grow, optimize and protect client organisations. We go beyond strategy, and provide end to end implementation of real-life data environments and have some of the best architects, project managers, business analysts, data scientists, big data engineers, developers and consultants in the region.
In this role as a Data Scientist you will be part of a culture that focuses on delivering excellence for our clients, whilst using cutting edge technologies. Part of your role will be to translate analytical solution outcomes in the context of business impacts and benefits, whilst working with diverse stakeholders to identify their challenges with data.
Your key responsibilities
- Determine the suitability and feasibility of an analytical solution for a given problem
- Review existing data sources to assess their applicability to address the business problem, and/or propose additional sources required for a solution
- Extract and manipulate data from a variety of sources and apply the appropriate pre-processing treatments for analysis
- Support the selection and configuration of analytical tools and infrastructure appropriate to our clients’ objectives, current and target state analytic maturity
- Design, develop and implement learning and/or optimisation solutions in areas that might include asset and inventory management, communications, channels and networks, risk and portfolio analysis, supply chain management and marketing effectiveness
- Design, develop and implement predictive models for areas such as customer segmentation, market basket analysis, offer propensity, demand planning & forecasting, fraud detection, inventory management and risk exposure
- Design, develop and implement approaches for productionising model scoring and the closed loop feedback paths required to support back-testing/test-and-learn model validation
- Apply visual analysis techniques and toolsets to extract patterns and meaning from data in a visual format
- Be involved in all aspects of the Project life-cycle, including Strategy, Road-Mapping, Architecture, Implementation and Development in order to gain maximum exposure to set you up for a successful consulting career
- Statistical analysis experience
- Algorithm design, implementation and operationalisation experience
- Development of statistical models, such as Bayesian, regression and linear optimisation models (ideally 5 Years)
- Development of machine learning models, including deep learning and graph applications (ideally 3 Years)
- Broad domain experience including Mining, with the ability to link the dots across industry data sets
- An eagerness to solve complex problems in environments that are often ambiguous, technologically challenged and require creative and lateral thinking
- A disciplined approach to problem solving and an ability to critically assess a range of information to differentiate true business needs as opposed to user requests
- An ability to work within a multidisciplinary team to seek requirements for analysis, output format and visualisation, and provide requirements to data engineers
- Fluency in at least one of the following programming languages R, Python, Scala
- Familiarity with the following data-related technologies Hadoop, Pig, Hive, Impala, SQL, Teradata, Oracle, SAS, MongoDB
- High-level understanding of architecting cloud-based solutions with the following products AWS Redshift/RDS, S3, EC2, Lambda, EMR, SageMaker, DynamoDB, Cloudformation, Athena, Kinesis – or equivalents in Azure or Google Cloud Platform is desirable
- Prior Big4 Consulting experience is highly desirable
- Experience in engaging with both technical and non-technical stakeholders
- Strong consulting experience and background, including engaging directly with clients
- Experience in a delivery role on Business Intelligence, Data Warehousing, Big Data or analytics projects
- Excellent interpersonal, oral and written communication skills with a knack for distilling complex and/or technical information for novice audiences