Said Tifaoui

- Lead discussions with Business Users - Build valid, efficient and effective models that can be easily productionized, either scheduled or user-triggered, with the correct level of sophistication based on expected business impact - Continuously monitor and validate model assumptions and performance by running test cases and error management strategies - Work with the IT team to productionize sufficiently mature models - Work with the process & operations team - Document code, procedures and results

- Identify areas where machine learning (statistical) would add business value - Lead discussions with Business Users to understand business processes - Build valid, efficient and effective models that can be easily productionized, either scheduled or user-triggered, with the correct level of sophistication based on expected business impact

• Elicit information from clients and gather inputs regarding their business problem • Write a proposal describing the approach to solve client’s business problem • Gather data and conduct analyses and write an insightful report • Communicate work progress with clients • Summarize the findings following a storytelling with data approach

• Planned and conduct elicitation session with stakeholders • Identified key stakeholders and conduct individual interviews with them • Determined whether stakeholders agree with the problem to solve • Gathered inputs for writing a business plan and presented it to stakeholders • Organized workshops to train leaders on the choice of business model

• Collaborated within the Scaling Problems in Statistics multidisciplinary group • Analyzed data to detect patterns of sales signals in the German retail industry • Used MySQL to query raw data • Conducted data cleaning and processing using R • Implemented machine learning algorithms (regression, classification) using R • Contributed to increasing public awareness of scaling problems in statistics

• Collaborated within the Scaling Problems in Statistics multidisciplinary group • Analyzed data to detect patterns of sales signals in the German retail industry • Used MySQL to query raw data • Conducted data cleaning and processing using R • Implemented machine learning algorithms (regression, classification) using R • Contributed to increasing public awareness of scaling problems in statistics

• Mitarbeit im Projekt: „The determinants of Halal meat consumption in Spain” • Selektion von Haushalten für Befragungen • Koordination von Fokusgruppen • Aufbereitung von Datenbanken • Empirische Untersuchung mit ökonometrischen Methoden

Actuarial Science

Fachrichtung Finanzwesen