Ilias Mokas Email & Phone Number

Copenhagen, Dk

Copenhagen, Capital Region, Denmark

As a Senior Data Scientist at Novo Nordisk, I lead the development and implementation of advanced analytics across the organization, fostering a data-driven culture under the initiative #bringdatatolife. Leveraging insights from mathematical, (GEN)AI, and econometric models, I enhance decision-making processes and drive business value.🤝 Collaborative Leadership• Team Collaboration: Partner with data scientists, data engineers, business analysts, and ML engineers to transform Proof of Concepts (PoCs) into scalable solutions.💰 Driving Business Value• Operationalization: Bring tangible business value by operationalizing machine learning models in real-world production environments (e.g., Marketing Mix Modeling for territory budget allocation, significantly impacting Novo Nordisk’s global regions and affiliates).Core Responsibilities• ML Pipelines: Establish robust pipelines for data ingestion, cleaning, and transformation, preparing data for advanced machine learning applications.• Insight Generation: Conduct explorative data and time series analysis to uncover actionable insights, driving strategic decision-making.• MLOps Capabilities: Utilize platforms like Databricks and Snowflake to build MLOps capabilities for seamless model deployment and management through CI/CD and version control using tools like Git.🔬 Innovative Hackathons• Developed classification models to segment user data, leading to targeted strategic recommendations to optimize user journeys and increase their engagement on the platform.• Developed GENAI chatbots, reducing SOP review times and assisting with quick answers, streamlining operational efficiency.

Hasselt, Flemish Region, Belgium

Flemish Region, Belgium

As a PhD researcher, I led groundbreaking research in virtual reality (VR) and advanced statistical modeling, driving significant advancements in understanding human preferences for non-market goods.🧪 Research and Experimentation • VR Experiment Development: Pioneered a VR experiment using the 3DUnity platform, comparing advanced statistical models (stated preference discrete choice models) and machine learning algorithms (convolutional neural networks, DNNs, clustering) to quantify and predict human preferences. • Data Analysis: Expertly collected, cleaned, and analyzed data using R-Studio and Python, ensuring high-quality and reliable results. • Experimental Design: Conducted rigorous experimental designs and A/B testing to measure respondent uncertainty between traditional surveys and VR, providing valuable insights into methodological effectiveness.📈 Impact and Contributions • On-Campus Experiment: Successfully organized a large-scale on-campus experiment with 200 participants, enhancing the research’s validity and impact. • Project Proposals: Contributed to three project proposals that secured funding for research, demonstrating the relevance and potential of the studies. • Supervision and Mentorship: Supervised two master’s theses, with students achieving high grades, reflecting the quality of guidance and support provided.🌍 Communication and Collaboration • Conferences and Collaborations: Presented research findings at six conferences and engaged in two research collaborations, showcasing effective communication skills and expanding professional networks.📚 Teaching and Skills • Teaching: Delivered courses in Microeconomics and Econometrics, imparting complex concepts and fostering a deep understanding in students. • Skills: Developed strong expertise in statistical modeling, and deep learning, applying these skills to advance research and analytical capabilities.

Santa Barbara, California, United States

- Developed a latent class logit models and deep neural networks (DNN) algorithms. I focus on evaluating model performance and developing a hybrid DNN-choice model that elicits interpretable coefficient estimates.- Develop a random parameter logit model to explain households’ decision to own electric vehicles.

Copenhagen Area, Denmark

- Conducted research at the Digitalization Department of CBS to classify sharing economy companies into categories based on attributes e.g. tight or loose control over participants.- Supervised students to develop machine learning algorithms (i.e., random forest).

Ispra, Italy

- Conducted applied econometric work (developed a fixed-effect model in R), using satellite data, to quantify the impact of climate change on coastal Sub-Saharan populations.- Collected and cleaned socio-economic data for the European Commission database. Created basic descriptive statistics in Tableau and R ggplot.

Athens, Greece

- Tracking and recording transactions - Payroll and cash desk management

Phd, Business Economics

Advanced Big Data Analytics In Python, Parallel Programming With R (Part Of My Phd Requirements)

Master Degree, Applied Economics

Master Degree, Engineering

Bachelor'S Degree, Economics And Finance

Activities and Societies: Basketball