Dorina Ababii
About me
I am passionate about the foundations of risk management, quantitative analysis, and data-driven financial strategies and their deployment and management in dynamic financial and banking environments.
Over the past years, I have worked extensively in both personnal and professional settings, combining my expertise in financial analysis, portfolio management, and data science to optimize risk mitigation strategies and enhance decision-making processes for investments.
I see the modern practice of a risk management professional as follows
Technically, I am deeply interested in
I am open to connecting for risk management, quantitative finance, and data-driven decision-making related topics.
Experience
Quantitative Finance | Data Science
Geneva, Switzerland
Key Role:
- Orchestrated a strategy to outperform the SPX index by conducting comprehensive research on systematic investment methods and market data analysis.
- Led portfolio management initiatives, focusing on risk analysis, machine learning integration, and data-driven investment strategies.
Technical Skills Applied:
- Tools/Technologies: Python (feature engineering, machine learning models), Bloomberg (portfolio tracking), Excel (data analysis).
- Methodologies: Implemented a Market Sentiment Indicator, leveraging feature engineering techniques and statistical models for decision-making.
- Systems/Platforms: Bloomberg Terminal, Python (data visualization and algorithm testing).
KEY INSIGHTS GAINED:
- Gained hands-on experience in applying machine learning models (e.g., Transformer) for financial forecasting and portfolio management.
- Improved ability to interpret large datasets to predict market trends and execute data-driven investment strategies.
- Developed proficiency in quantitative finance, combining statistical analysis and algorithmic trading.
RELEVANCE AND FUTURE APPLICATION:
- Tools/Technologies: Python (feature engineering, machine learning models), Bloomberg (portfolio tracking), Excel (data analysis).
- Methodologies: Implemented a Market Sentiment Indicator, leveraging feature engineering techniques and statistical models for decision-making.
- Systems/Platforms: Bloomberg Terminal, Python (data visualization and algorithm testing).
KEY INSIGHTS GAINED:
- Gained hands-on experience in applying machine learning models (e.g., Transformer) for financial forecasting and portfolio management.
- Improved ability to interpret large datasets to predict market trends and execute data-driven investment strategies.
- Developed proficiency in quantitative finance, combining statistical analysis and algorithmic trading.
RELEVANCE AND FUTURE APPLICATION:
Building on a strong foundation in financial modeling and machine learning, I honed the ability to optimize investment strategies and mitigate portfolio risks. By applying sentiment analysis and data-driven indicators, I enhanced real-time investment decision-making, ensuring the delivery of accurate and timely insights. These skills reinforce my ability to contribute effectively to financial processes and drive strategic decisions in diverse financial environments.
Junior Financial Analyst
Geneva, Switzerland
Research Analyst
Geneva, Switzerland
Credit Analyst Intern
Chisinau, Republic of Moldova
Key Role:
- Collected and verified financial and personal information as part of the KYC (Know Your Customer) process, ensuring compliance with regulatory standards
- Conducted thorough analyses of credit data and financial documentation to assess the creditworthiness of individual and corporate loan applicants
- Worked closely with senior credit analysts to evaluate credit history, financial statements, and market conditions for comprehensive credit risk assessments, especially for corporate clients
Technical Skills Applied:
- Tools/Technologies: KYC verification platforms, Microsoft Excel (data analysis), Bank’s internal risk management software
- Methodologies: Applied KYC procedures, credit risk analysis, and financial data validation to meet regulatory requirements
- Systems/Platforms: Leveraged customer onboarding and due diligence systems for identity verification and risk assessment
KEY INSIGHTS GAINED:
- Gained anunderstanding of KYC procedures, including customer identity verification, background checks, and compliance with anti-money laundering (AML) regulations
- Enhanced skills in interpreting complex financial statements and cross-checking personal financial details to ensure compliance with financial regulations and company policies
- Developed a thorough understanding of corporate credit risk by analyzing financial reports, market conditions, and credit histories
RELEVANCE AND FUTURE APPLICATION:
This experience enhanced my expertise in regulatory compliance and customer due diligence, both crucial for maintaining financial integrity.
It advanced my ability to navigate KYC and AML requirements, integral to ensuring compliance and reducing risk in financial institutions.
The knowledge gained in customer verification and risk assessment supports effective decision-making in critical areas such as risk management, fraud detection,
and compliance-driven operations.
Technical Skills Applied:
- Tools/Technologies: KYC verification platforms, Microsoft Excel (data analysis), Bank’s internal risk management software
- Methodologies: Applied KYC procedures, credit risk analysis, and financial data validation to meet regulatory requirements
- Systems/Platforms: Leveraged customer onboarding and due diligence systems for identity verification and risk assessment
KEY INSIGHTS GAINED:
- Gained anunderstanding of KYC procedures, including customer identity verification, background checks, and compliance with anti-money laundering (AML) regulations
- Enhanced skills in interpreting complex financial statements and cross-checking personal financial details to ensure compliance with financial regulations and company policies
- Developed a thorough understanding of corporate credit risk by analyzing financial reports, market conditions, and credit histories
RELEVANCE AND FUTURE APPLICATION:
- Gained anunderstanding of KYC procedures, including customer identity verification, background checks, and compliance with anti-money laundering (AML) regulations
- Enhanced skills in interpreting complex financial statements and cross-checking personal financial details to ensure compliance with financial regulations and company policies
- Developed a thorough understanding of corporate credit risk by analyzing financial reports, market conditions, and credit histories
RELEVANCE AND FUTURE APPLICATION:
This experience enhanced my expertise in regulatory compliance and customer due diligence, both crucial for maintaining financial integrity. It advanced my ability to navigate KYC and AML requirements, integral to ensuring compliance and reducing risk in financial institutions. The knowledge gained in customer verification and risk assessment supports effective decision-making in critical areas such as risk management, fraud detection, and compliance-driven operations.
Accounting Intern
Chisinau, Republic of Moldova
Key Role:
- Managed the generation of monthly invoices and ensured timely processing of accounts payable and accounts receivable;
- Conducted financial data analysis and prepared balance sheets and income statements for senior management to aid in financial reporting and decision-making;
- Processed employee payroll using 1C Enterprise accounting software, ensuring accuracy and adherence to payroll schedules.
Technical Skills Applied:
- Tools/Technologies: 1C Enterprise (accounting software), Excel (financial data analysis), Financial reporting tools
- Methodologies: Methodologies: Applied principles of financial accounting, including balance sheet preparation, income statement generation, and payroll management
- Systems/Platforms: Systems/Platforms: 1C Enterprise for payroll and financial data processing, Microsoft Excel for financial statement preparation and data analysis
KEY INSIGHTS GAINED:
- Gained hands-on experience in managing essential accounting processes such as accounts payable/receivable, financial reporting, and payroll processing;
- Developed a solid understanding of financial data structuring, particularly in the preparation of balance sheets and income statements, which provided insights into the financial health of the company;
- Improved proficiency in using accounting software for operational efficiency, ensuring timely and accurate financial reporting and payroll administration.
RELEVANCE AND FUTURE APPLICATION:
This experience gave me a solid understanding of essential accounting processes like managing accounts payable/receivable and preparing financial reports. It also improved my skills in handling payroll and using accounting software efficiently. These skills have strengthened my attention to detail and accuracy in managing financial data and processes, which are essential for maintaining clarity and precision in any financial context.
Technical Skills Applied:
- Tools/Technologies: 1C Enterprise (accounting software), Excel (financial data analysis), Financial reporting tools
- Methodologies: Methodologies: Applied principles of financial accounting, including balance sheet preparation, income statement generation, and payroll management
- Systems/Platforms: Systems/Platforms: 1C Enterprise for payroll and financial data processing, Microsoft Excel for financial statement preparation and data analysis
KEY INSIGHTS GAINED:
- Gained hands-on experience in managing essential accounting processes such as accounts payable/receivable, financial reporting, and payroll processing;
- Developed a solid understanding of financial data structuring, particularly in the preparation of balance sheets and income statements, which provided insights into the financial health of the company;
- Improved proficiency in using accounting software for operational efficiency, ensuring timely and accurate financial reporting and payroll administration.
RELEVANCE AND FUTURE APPLICATION:
- Gained hands-on experience in managing essential accounting processes such as accounts payable/receivable, financial reporting, and payroll processing;
- Developed a solid understanding of financial data structuring, particularly in the preparation of balance sheets and income statements, which provided insights into the financial health of the company;
- Improved proficiency in using accounting software for operational efficiency, ensuring timely and accurate financial reporting and payroll administration.
RELEVANCE AND FUTURE APPLICATION:
This experience gave me a solid understanding of essential accounting processes like managing accounts payable/receivable and preparing financial reports. It also improved my skills in handling payroll and using accounting software efficiently. These skills have strengthened my attention to detail and accuracy in managing financial data and processes, which are essential for maintaining clarity and precision in any financial context.
Education
CAS in Risk Management
Zürich, Switzerland
GPA: 6/6
COURSE OBJECTIVE:
- Focused on identifying, measuring, and mitigating financial and non-financial risks in banking and finance;
- Covered current challenges in risk governance, sustainability, and digital assets management.
PROFICIENCIES ACQUIRED:
- Tools/Technologies: Risk measurement techniques, financial instruments, derivatives;
- Methodologies: Stress testing, credit risk assessment, regulatory compliance.
Key Insights Gained:
- Learned advanced risk management strategies and governance frameworks in the financial sector;
- Developed a solid understanding of financial instruments for risk mitigation.
Relevance and Future Application:
This program has strengthened my ability to manage risk effectively in banking and finance sectors, especially regarding emerging risks related to sustainability and digital assets.
MSc. Banking and Finance | Capital Markets & Data Science
Zürich, Switzerland
COURSE OBJECTIVE:
- Focused on advanced quantitative skills, including quantitative investment strategies, machine learning, and risk management;
- Leveraged data science techniques to optimize decision-making in capital markets.
PROFICIENCIES ACQUIRED:
- Tools/Technologies: Python, machine learning algorithms, deep learning models;
- Methodologies: Quantitative investment strategies, data-driven risk management.
KEY INSIGHTS GAINED:
- Enhanced my ability to apply data science in financial markets to optimize investment strategies;
- Gained experience in integrating sustainability into financial analysis.
Relevance and Future Application:
The skills gained in this program will help me navigate modern finance, with a focus on data-driven decision-making in capital markets and risk management.
BSc. Economics
Rouen, France
COURSE OBJECTIVE:
- Gained in-depth knowledge of theoretical and empirical economic principles;
- Focused on microeconomics, macroeconomics, econometrics, and statistics;
- Developed an understanding of economic behavior, policy, and market dynamics.
PROFICIENCIES ACQUIRED:
- Tools/Technologies: Econometric modeling, statistical software, data analysis tools;
- Methodologies: Applied quantitative methods to evaluate economic policies and market structures.
Key Insights Gained:
- Developed strong analytical skills in interpreting economic data and market dynamics.
Relevance and Future Application:
This program equipped me with the analytical tools necessary to evaluate economic trends and policies, preparing me for research roles and policy analysis in economics.
BSc. Economics (1st Year)
Reims, France
COURSE OBJECTIVE:
- Studied core economic principles, focusing on microeconomics, macroeconomics, and financial markets;
- Explored the relationship between economic policies and their societal impacts;
- Laid the foundation for understanding strategic management in economics and business contexts.
PROFICIENCIES ACQUIRED:
- Tools/Technologies: Quantitative analysis, financial modeling, economic forecasting;
- Methodologies: Microeconomic theory, macroeconomic policy analysis, and market analysis.
Key Insights Gained:
- Developed a comprehensive understanding of financial markets and their role in the economy.
Relevance and Future Application:
This year provided a solid foundation in economics, which sharpened my analytical skills and deepened my understanding of market dynamics, crucial for addressing economic challenges in various sectors.
High School, Profile in Sciences and Accounting
Chisinau, Republic of Moldova
PROFICIENCIES ACQUIRED:
- Studied science subjects (math, physics, chemistry) along with professional accounting principles;
- Gained hands-on experience in bookkeeping, financial statements, and auditing procedures.
KEY INSIGHTS GAINED:
- Tools/Technologies: Accounting software, bookkeeping systems;
- Methodologies: Applied accounting standards and scientific problem-solving techniques.
Key Insights Gained:
- Developed a strong foundation in both accounting and scientific analysis techniques.
Relevance and Future Application:
This program provided a unique combination of accounting and science skills, helping me excel in managing complex financial and technical challenges.
Projects
RESUME IN WET FORMAT USING GITHUB PAGES
Web Development, Front-End Design
Developed a professional resume in the WET (Web Experience Toolkit) format and hosted it on GitHub Pages, ensuring compliance with accessibility and usability standards. Applied HTML, CSS, and JavaScript to create a responsive, user-friendly interface, enhancing accessibility through WET components.
PROJECT OVERVIEW:
- Created a professional, interactive resume in WET (Web Experience Toolkit) format, hosted on GitHub Pages
- Integrated HTML, CSS, and JavaScript to ensure a responsive and user-friendly interface, enhancing accessibility through WET’s built-in components
TECHNICAL SKILLS APPLIED:
- Tools/Technologies: HTML, CSS, JavaScript, GitHub Pages, WET Toolkit
- Methodologies: Responsive web design, accessibility compliance, front-end development
KEY INSIGHTS GAINED:
- Developed expertise in using the WET framework, ensuring accessibility compliance in web development projects
- Enhanced skills in version control using GitHub, and in deploying websites using GitHub Pages
RELEVANCE AND FUTURE APPLICATION:
This project honed my web development skills and deepened my understanding of accessibility and usability standards, particularly valuable for government and public sector web development projects.
How can AI be leveraged to enable CRO employees to work more efficiently?
CRO, Compliance
Streamlining, harmonizing, translating, and updating legal client forms using advanced analytics techniques (e.g., Large Language Models (LLMs), AI, Optical Character Recognition (OCR), and Natural Language Processing (NLP)
Master's Thesis: Machine Learning in Asset Pricing
Asset Management, Portfolio Management, Data Science
Explored the use of OLS, LSTM, and CatBoost for asset pricing, specifically in regional and global portfolio management. Executed experiments using international stock data from 2000-2021, split into development and testing phases. Gathered stock data from Refinitiv and macroeconomic indicators from FRED, applying Pearson-Correlation for feature selection. Demonstrated that deep learning models, like LSTM, outperform linear models in predictive accuracy and highlighted the role of explainable AI in improving portfolio management strategies.
Text classification and analysis
Sentiment Analysis, Natural Language Processing (NLP)
Developed and evaluated multinomial Naive Bayes and neural network models for text sentiment analysis using a Kaggle dataset. Assessed model performance, focusing on accuracy and effectiveness in classifying sentiments. Explored practical applications of sentiment analysis across marketing, finance, and social media, showcasing its impact on decision-making and customer insights. Demonstrated proficiency in Python for text processing and model development.
PROJECT OVERVIEW:
TECHNICAL SKILLS APPLIED:
KEY INSIGHTS GAINED:
Strengthened proficiency in text classification, with a focus on leveraging machine learning for real-world sentiment analysis applications
RELEVANCE AND FUTURE APPLICATION:
This project enhanced my ability to apply NLP techniques for sentiment analysis, providing valuable insights for businesses in decision-making and customer relationship management.
Credit Card Fraud Detection
Risk Management, Compliance, KYC
Developed a machine learning solution to detect fraudulent credit card transactions, addressing a critical issue causing billions in losses annually. Applied algorithms such as K-Nearest Neighbor (KNN), Logistic Regression, Support Vector Machine (SVM), and Decision Tree to a large, anonymized dataset. Ensured due diligence through rigorous model evaluation, focusing on accuracy, minimizing false positives, and enhancing compliance with data privacy standards. Proposed improvements integrating location data for future fraud detection enhancements, emphasizing risk management and security. Demonstrated expertise in data analysis, machine learning, and fraud prevention.
Testing for heteroskedasticity, multicollinearity, serial autocorrelation
Statistics, Data Analysis
Collected and organized stock and economic data to build a comprehensive database for analysis. Conducted OLS regression to analyze stock returns, optimizing models based on R² values. Ensured accuracy and reliability by testing for heteroscedasticity, normality, autocorrelation, and addressing multicollinearity. Demonstrated strong skills in statistical analysis and data integrity in financial modeling.
Switzerland’s Financial System and Real Economy Interplay During the Pandemic
Statistics, Data Analysis
Analyzed historical data to model the Swiss economy’s response to financial shocks during the pandemic. Developed and tested financial models to forecast business cycles and assess the impact on Switzerland's real economy. Demonstrated expertise in macroeconomic analysis and financial forecasting in times of crisis.
CFA Challenge
Statistics, Data Analysis
University level competition
Conducted a comprehensive financial analysis of a single stock to assess its buy, hold, or sell potential. Applied financial theories and valuation techniques to evaluate the stock's performance and risk profile. Demonstrated proficiency in financial modeling and risk assessment, providing clear investment recommendations in a competitive academic environment.
Skills
- Decision Trees (DT)
- CatBoost
- Random Forests (RF)
- Principal Component Analysis (PCA)
- k-Nearest Neighbors (k-NN)
- Logistic Regression
- Logic Regression
- Support Vector Machines (SVM)
- Transformers
- Data Collection & Preprocessing
- Feature Engineering & Selection
- Model Development & Validation
- Financial Data Analysis & Interpretation
- Model Deployment & Monitoring
Interests
Outside of my work in finance and data science, I have a passion for creative writing, particularly poetry, which allows me to explore ideas beyond the numbers. I also have a keen interest in behavioral finance and sustainability, always looking for ways these fields intersect with the evolving financial landscape.
When I’m not deep into financial models or research, I enjoy spending time outdoors, whether it's hiking or exploring new places. Indoors, I love diving into books, honing my cooking skills, and keeping up with the latest trends in data science and technology.
Awards & Certifications
- 1st Place - RiskON Hackaton, University of Zurich, 2024
- Business Concept May, Innosuise, 2022
- Refinitiv Eikon, Refinitiv, 2021
- Bloomberg Market Concepts, Bloomberg, 2020
- Les Entrep’, Association Nationale Les Entrepreneuriales, 2020