What you do You will be in charge of carrying out the analysis of the historical and prevailing fraud trends and develop predictive models that will enable better pro-active fraud detection & prevention (introducing new data-driven internal controls) and provide a decision support for more informed and data backed decisions. Define and develop data structures, business requirements and report in claims and payment processes across all lines of business for Allianz Partners with an objective of detecting potential fraudulent claims and leakages. Build data models, business rules and real time triggers to identify fraudulent patterns that can lead to detection of potential Frauds or suspicious transactions Collect data from diverse systems, represent it digitally in an effective manner making it suitable for model building to detect abnormal patterns for detection of frauds. Partner with Basinets Units and Global office business stakeholders, Fraud coordinators to identify potential weaknesses in processes and systems which can lead to fraud and leakages. Develop end-to-end solutions which includes simulation of modeling results and insights to business stakeholders, estimation of business impact and expected benefits Prepare different reporting formats for presentation of modeling results to end-users such as reports, scorecards, dashboards, web applications as requested by lines of business Performs research on new modeling algorithms, modeling concepts, or technical tools to identify suitable techniques for anti-fraud management Work with Allianz Group GAFS Anti-fraud and data science teams to strengthen controls in various tools used by Operations. Train users and business stakeholders to interpret modeling results and use them for decision making.

What you bring Degree in a quantitative discipline such as statistics, computer science, mathematics, or machine learning and extensive work experience in a relevant industry You have to be proactive and experienced in coding and predictive modeling using large and complex datasets in a business setting You will need the capability to develop and deploy data science solutions and create values with limited guidance Assert yourself in verbal and written communications skills, listening and teamwork skills, and effective presentation skills You should bring with you a substantial experience in several programming languages like Python, R, SQL, even Spark, that allows you to extract and transform data from a variety of data sources such as Oracle, SQL, Hadoop and experience with data visualization such as Spotfire or Tableau Manage and manipulate large, complex datasets and ability to assess and interpret moderate to complex concepts