Driss Mouiha
Munich
Summary
Experienced Data Scientist with a strong background in the banking and operational industries, specializing in audit. Proficient in using tools like Python, R, SAS, SQL, AWS and Power BI to uncover insights, create impactful visualizations, and streamline processes. Skilled in automating workflows and delivering cost-saving solutions. Willing to bring my expertise to new industries, with a commitment to continuous learning and driving meaningful advancements.
Overview
3
3
years of professional experience
Work History
Data Scientist (Visa Sponsored)
Sixt SE (Car Rental)
12.2024 - Current
- Designed and developed interactive dashboards using AWS Athena (SQL PRESTO) and QuickSight to enable the internal audit team to effectively monitor and audit Sixt activities.
- Detecting internal and external fraud by analyzing customer and employee behaviors, utilizing Python and advanced data science techniques.
- Produced actionable insights to enhance operational efficiency and reduce costs.
- Automated routine tasks and workflows for colleagues, improving productivity and consistency in internal audit processes.
- Collaborated closely with the internal audit team to identify inefficiencies and propose data-driven strategies to mitigate risks and enhance cost management.
Data Scientist
Desjardins Bank
05.2022 - 12.2024
- Fraud and anomalies detection with structured and unstructured data using decision trees, KNN, K-means, Isolation Forest and IQR method ( Python packages: matplotlib, NLTK, pandas, Scikit-learn, seaborn, Numpy and Keras)
- Advisory role in internal audit such as being able to create more than $300 million unused money for investments by analyzing quarterly financial statements
- Producing an app to find differences in conformities and legal texts changes from the previous years ( times of difference detection reduced to 90%)
- Automating Risk and Non-Conformity Analysis to support advisors and audit teams in time-consuming audit mandates.
- Support to advisors in data cleaning and data representation for complex unstructured data using RStudio packages such as tidyverse, dyplr, tidyr, lubridate and more
- Vulgarizing data to non-data users and presenting the multiple projects to team managers, directors and vice-presidents
- Very good ability to communicate clearly the results to other team members or executives.
- Produced high-quality model documentation for clear presentation to both technical and non-technical audiences.
Data Analyst Intern
Ministry of Education
01.2022 - 05.2022
- Data analysis of different school institutions performance for native nation in Quebec
- Production of statistical indicator of the students education
- Comparing the education of different ethnic groups and finding the factor that affects their education ( ANOVA was mostly used).
Data Analyst Intern
Canada Economic Development
09.2021 - 12.2021
- Identification of late payroll using mathematical models
- Analyzing data and creating statistical indicators to detect regions in Canada that need financial support.
Education
Bachelor of Science (B.S.) - Statistics
Laval University
International Baccalaureate - Applied Sciences
François-Xavier Garneau College
Skills
- Data analytics
- RStudio, SAS, Python, SQL & Power Bi
- Machine learning & AI
- Shiny apps
- Internal audit
- Automation
- Banking conformity and finance
- Communication and vulgarization
- Problem solving
- Statistical analysis
- Pragmatic
- Googling
Accomplishments
- Anomaly detection in financial banking data (Desjardins Bank): Used data reduction techniques and unsupervised learning with an encoder-decoder method for scalable anomaly detection without labeled data.
- Optimizing cash reserves in various bank branches (Desjardins Bank): Employed R for statistical analysis to study cash reserve trends, identify unused amounts, and simulate reallocating them to optimize use and interest income.
- Advanced identification of duplicates in tax credit programs (Desjardins Bank): Utilized Python for precise duplicate analysis using Term Frequency-Inverse Document Frequency and cosine similarity score.
- Strategic wind turbine placement study in Canada (INRS & Laval University): Analyzed historical wind speed data with SAS, investigated wind-climate associations, classified sites, and forecasted wind speed for thirty years using time series analysis.
Languages
English
Proficient (C2)
French
Bilingual or Proficient (C2)
Arabic
Native
Spanish
Intermediate (B1)
Additional Information
- Nationality : Canadian
- Work and residence permit: EU blue card
Timeline
Data Scientist (Visa Sponsored)
Sixt SE (Car Rental)
12.2024 - Current
Data Scientist
Desjardins Bank
05.2022 - 12.2024
Data Analyst Intern
Ministry of Education
01.2022 - 05.2022
Data Analyst Intern
Canada Economic Development
09.2021 - 12.2021
International Baccalaureate - Applied Sciences
François-Xavier Garneau College
Bachelor of Science (B.S.) - Statistics
Laval University
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