This is an exciting opportunity for someone currently working in the world of data. If you are an ambitious professional with a long experience in data analysis, data science, analytics, crazy for business intelligence and looking to take on a challenge, this could be the opportunity you’ve been waiting for.
As Fraud Analytics Business Leader in the Antifraud Team, you will draw and drive the data strategy of the department, will “slice and dice” customer data to gather business insight and will help the company taking market advantages from the prevention of frauds, the detection of risks and the reduction of losses through the use of data, designing better solutions and driving the change.
Passionate about technology and data and able to transfer it to other people.
Strong problem solving and critical thinking skills, and the creativity to find and try new solutions.
Strong understanding of planning issues, resource allocation, and priority setting.
Build knowledge of the data held and its structure.
Drive the data strategy and the data roadmap of the department.
Facilitate the communication with the other data teams in the company to easy the cross fertilization of data knowledge.
Work in a manner that aligns with timelines, budgets and quality expectations.
Effectively interact with senior management.
Manage the roadmap of projects to take advantage from the use of data.
Analyze trends to discover new patterns of frauds and implement improvement to the fraud model.
Support the governance and the reporting about business results of the department and help to exceed expectations.
Ease the selection of new data sources preditcive for fraud prevention and detection.
Skills and experience
A Master’s degree in Engineering, Statistics, Economics, Maths or equivalent.
A background of working with large amounts of data.
A minimum of 5 years of working experience in data analysis in solid corporations or consulting to analyse and gather insights from data.
A strong experience with an analytical software package (SAS & SQL, R or similiar).
Experience of effective ownership of multiple projects of varying scale.
Nice to have
Machine learning/Predictive modeling.