We are currently seeking highly motivated people for our Advisory practice, which is a leading provider of services to financial industry and large corporate clients of all industries. Being part of our Data & Analytics Center of Excellence you will work with multi-disciplinary teams across the entire EMEIA region to support global clients.
You will identify appropriate modeling techniques to answer the most critical business questions and use your analysis to infer well substantiated business insights in support of your clients’ decision making. To do that, you will use clients’ in-house data as well as appropriate external data-sources. You will also resort to various data management and visualization techniques to provide insight into the data. Your portfolio of skills covers a wide range of advanced statistical and machine learning techniques for classification, prediction, recommendation, clustering, forecasting, as well as data management, data visualization, and optimization, applied in a commercial context.
You will build valued relationships with external clients and internal peers and contribute to the development of a portfolio of business by focusing on high-impact opportunities. You will contribute to presentations of modeling results and project proposals. Bringing experience and unique insight on one or more industry sectors, such as for example Telecommunications, Consumer Products, Retail, Healthcare/Life Sciences, Financial Services, Oil & Gas, Power & Utilities, Government & Public Sector, Automotive and on at least one of the following functions: Finance, Supply Chain, Customer, Social Media, Risk & Compliance, you will use your knowledge and experience to shape solutions to client problems. As a respected professional, you will communicate effectively with EY engagement partners and managers and contribute to building, managing and motivating high-performing teams.
- Excellent academic background, including at a minimum a bachelor or a masters degree in Data Science, Business Analytics, Statistics, Mathematics, Econometrics, Engineering, Operational Research, Computer Science, or other related field with strong quantitative focus.
- 2-7 years of working or related research experience (evidenced by PhD and/or relevant publications, awards, or completed project credentials) with preferably at least 2 years in a commercial/industrial context and particular focus on the following:
- Data modeling and Management, integration and manipulation of large disparate datasets (i.e. structured, semi-structured or unstructured)
- Predictive modeling and optimization
- Strong skills in databases, statistical packages for data manipulation and in development of predictive and prescriptive models (i.e. R, Python, SAS, SPSS, SQL).
- Experience in designing, building, testing and validating models using a large number of statistical and other quantitative techniques.
- Strong written and verbal communication, presentation, client service and technical writing skills in English for both technical and business audiences.
- Fluent English is a pre-requisite. Knowledge of additional languages will be appreciated.
- Strong analytical, problem solving and critical thinking skills.
- Ability to work under tight timelines for multiple project deliveries.
- Ability/flexibility to travel and work abroad for international projects.
Additionally, the following will be considered a strong asset:
- Software development experiences in Java and/or C/C++ as well as advanced databases.
- Experience with Big Data/In Memory technologies, such as Hadoop (Hortonworks, Cloudera etc.), SAP HANA, IBM BigInsights, Oracle Exalytics.
- Experience with scalable big data based advanced analytics software, such as Apache Mahout or 0xdata H2O.
- Experience in Advanced Data Visualization tools, such as Tableau, Spotfire, Qlikview and others for integration between disparate data sources, design and implementation of KPIs and generation of automatic and scalable visualizations that will facilitate extraction of business insights.
- Experience in structuring and overseeing program design, development, testing and debugging activities.