Dorina
Ababii

Portfolio Management / Investment Role

HCP Asset Management · Geneva, Switzerland

• [ INVESTMENTS ]
• [ DATA SCIENCE ]
• [ PORTFOLIO RISK MANAGEMENT ]
• [ PORTFOLIO MANAGEMENT ]

• Worked across the development, implementation, monitoring, and operational management of systematic equity investment strategies within live-capital environments.
• Contributed to the design, launch, and management of systematic equity AMCs, supporting portfolio construction frameworks, allocation logic, factor exposure analysis, and ongoing performance evaluation across different market environments.
• Developed machine-learning-based investment models and systematic research frameworks from ideation through validation, deployment, monitoring, and continuous enhancement.
• Built automated Python-based research and analysis pipelines covering data sourcing, feature engineering, model validation, reporting automation, and investment process transparency.
• Worked across the full investment workflow, combining quantitative research, portfolio analytics, investment implementation, and operational portfolio management responsibilities.
• Participated in institutional sales support and investor communication activities, including preparation of investment materials, reporting, and strategy presentations for internal and external stakeholders.
• Used machine learning and AI tools daily to improve research workflows, automate repetitive tasks, structure information, and increase efficiency across investment-related processes.
• Worked at the intersection of investments, quantitative analytics, technology, and stakeholder-facing activities, translating quantitative investment processes into structured and actionable investment narratives.

Credit Analyst Intern

Mobiasbanca Groupe Société Générale · 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

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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 an understanding 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

Vremealux · 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.

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Technical Skills Applied

• Tools/Technologies: 1C Enterprise (accounting software), Excel (financial data analysis), Financial reporting tools
• Methodologies: Applied principles of financial accounting, including balance sheet preparation, income statement generation, and payroll management
• 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.

CAS in Risk Management

University of Zürich · 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.

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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 University of Applied Sciences · 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.

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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

University of Rouen Normandie · 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.

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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)

University of Reims Champagne-Ardenne · 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.

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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

CNC of ASEM · 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.

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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.

Resume in WET Format Using GitHub Pages

Personal Project · 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.

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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?

Winner Team RiskON @ University of Zürich · 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

Zürich University of Applied Sciences · 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

Zürich University of Applied Sciences · 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.

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Project Overview

• Developed and evaluated Multinomial Naive Bayes and neural network models for text sentiment analysis using a Kaggle dataset
• Assessed model performance based on accuracy and effectiveness in classifying sentiments
• Explored practical applications of sentiment analysis in marketing, finance, and social media, demonstrating its impact on decision-making and customer insights

Technical Skills Applied

• Tools/Technologies: Python, Multinomial Naive Bayes, neural networks, Kaggle datasets
• Methodologies: Applied sentiment analysis, NLP techniques, and model evaluation metrics

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

Zürich University of Applied Sciences · 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

Zürich University of Applied Sciences · 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

Zürich University of Applied Sciences · 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

Zürich University of Applied Sciences · 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.