Dorian Lagadec

As a Data Strategist at Morgan Stanley, I supported and enhanced the work of two teams. My efforts were split between a global data engineering department and a team dedicated to US electronic rates in NYC.

🔹 Key Contributions:

🔍 Data Engineering:

Collaborated with a global team to deliver unified, low-latency data applications, enabling seamless data cataloging, querying, analysis, and curation across desks. Ensured data quality for optimal decision-making.

📈 Trading Systems:

Supported the development of systematic trading and hedging systems for the US rates team, enhancing traders' ability to leverage statistical signals. My machine learning research directly contributed to PnL improvement.

🛠️ Process Improvement:

Assisted in the adoption of best practices for coding, documentation, testing, and continuous delivery within the trading team, promoting more efficient development methodologies.

🤝 Collaboration:

Facilitated teamwork between global teams, including data engineers, software engineers, modelers, and risk managers, ensuring the success of complex projects.

🔹 Skills and Technologies:

💡 Soft Skills:

Enhanced my skills in teamwork, project management, and communication with diverse profiles.

🔧 Technical Skills:

Refined my skills in data science, data engineering, Linux, Bash, Python, various databases, and full-stack development.

🔹 Personal Growth:

This role transformed me from a data scientist into a seasoned full-stack developer, capable of contributing to all stages of a project's lifecycle. It also honed my communication and collaboration skills with experts from various fields.

At Kanopy AM, a Parisian investment firm specializing in mid-to-large cap European equities, I played a key role in bridging investment ideas with concrete strategies. In collaboration with the Chief Investment Officer, Chief Technology Officer, and Portfolio Manager, I translated innovative research into practical investment strategies and managed a team of a few junior data scientists.

🔹 Key Achievements:

📊 Project Contributions:

Responded to calls for projects from major European insurers by translating conceptual ideas into rigorously tested investment algorithms for low-frequency decisions.

🛠️ API Development:

Created APIs to enable the research team to efficiently query company data, thereby accelerating the research process.

📈 Strategy Testing:

Tested numerous investment strategies based on statistical and behavioral finance research, refining our approach with empirical insights.

🚀 New Allocation Regime:

Developed and deployed a new allocation regime using Docker, enhancing our investment process with modern technologies.

📚 Skill-Up and Training:

Contributed to the team's machine learning upskilling and gave a lecture to finance students alongside the CIO.

🔹 Skills and Technologies:

💬 Soft Skills:

Excellence in communication, collaborating with financial experts, sales, marketing, and technical teams.

🔧 Technical Skills:

Acquired in-depth knowledge of finance, European regulations, portfolio management, as well as technical skills in Python, Django, Docker, and Bash.

At Avisia, within the Risk department, I contributed to impactful data science projects that strengthened our clients' capabilities and provided valuable insights. My role involved modernizing algorithms, developing interactive tools, and training consultants.

🔹 Key Achievements:

🏦 Credit Scoring Modernization:

For a French consumer bank, I used Dataiku DSS to modernize the credit scoring algorithm. I demonstrated that a simpler solution could replace the existing algorithm quickly and improved scoring metrics with advanced tree-based regressions.

📊 Interactive Dashboard:

Created an interactive dashboard for a French public institution using graph theory and visualization to highlight trends and patterns in fake reviews on Google Reviews and TripAdvisor.

📚 Consultant Upskilling:

Led internal workshops on natural language processing and Blockchain to train consultants, enhancing their ability to seize new business opportunities for the company.

🔹 Skills and Technologies:

💬 Soft Skills:

Developed consulting skills, including diagnosing client issues and proposing high-value solutions. Improved my ability to communicate complex concepts effectively through internal training sessions.

🔧 Technical Skills:

Gained hands-on experience with Python, SQL, Dataiku DSS, and APIs, deepening my technical expertise in data science.

🔹 Personal Growth:

This role marked a crucial transition from university to industry, deepening my understanding of risk management and demonstrating how data science can provide practical, concrete solutions.