My client a leading Big 4 consultancy is currently searching for a Data analytics consultant to join them on a permanent basis in there London office.
There searching for Data Analytics professionals with experience in Financial Services focused on Asset Management or Wealth management, this will be an excellent opportunity for you to join a successful team at a time of growth. There strengthening their data and analytics capabilities in Financial Services as their clients face significant shifts in the regulatory environment
Experience of the UK Financial Services industry – ideally in Asset and Wealth Management
Understanding relevant Financial Services regulation (e.g. MIFID II, EMIR, AML, Dodd-Frank, FATCA, and Solvency II)
Understanding of the Business Value Chain
Experience in building Artificial Intelligence and Machine learning models e.g. Natural Language Processing (NLP), Natural Language Generation (NLG), Deep Learning (Voice and Image recognition), Geospatial Prediction, Multi-layer Perceptron and other Neural Networks.
Artificial Intelligence / Voice Technology experience e.g. IBM Watson, Amazon Echo, Google Home, Microsoft Cortana, Apple Siri.
Experience in multiple tools/language/frameworks within the Big Data (Hadoop, Spark, Hive, MongoDB, Neo4j, Hbase, Cassandra)
Understanding of Artificial Intelligence and Cloud Platforms (e.g. Azure / IBM / Google)
Advanced data analytics, building models in Python, R, SAS programming languages and libraries
Data analytics and visualisation products such as D3, Power BI, Qlikview, Tableau
Strong SQL and data manipulation skills
Data quality and data cleansing techniques
Understanding of the principles of data governance
Developing and implementing information led data transformation programmes
Creating Innovation Hubs for clients – changing the way they think
Designing and developing dashboards, visualisations and metrics to improve understanding of business processes, identify potential weaknesses and provide operational resilience
Developing data analytics routines to test detection scenario
Designing automated and data-driven controls to better manage and protect data assets
Validating and testing data and reports submitted to regulatory bodies
Assessing and optimizing data governance processes and operations