About me

Hi, I'm Yitong (Jennifer) Li, a passionate Data Scientist and Researcher with a background in Data Science and Psychology. I specialize in machine learning, deep learning, and natural language processing. My work focuses on leveraging data-driven insights to solve real-world problems, particularly in recommendation systems and AI fairness.

I am deeply passionate about data-driven business analysis, using analytical approaches to uncover insights that drive strategic decision-making. My goal is to merge my expertise in machine learning and data science with real-world business applications, ultimately advancing my journey to becoming a professional data scientist. By continuously exploring new technologies and refining my analytical skills, I aim to contribute to impactful solutions that optimize business performance and user experiences.

Technical Skills

  • Python Logo

    Python

    Developed machine learning and deep learning models, including recommender systems using transformer-based architectures (BERT, LoRA, DistilBERT), automated usability testing scripts (Selenium), chatbot development (GPT-2), and predictive analytics for identifying high-risk mental health patients.

  • R studio Logo

    R Studio

    Utilized tidyverse and lme4 packages for statistical modeling, mixed-effects models, quantitative analyses, and done machine learning and statistical testing in academic researches.

  • MySQL

    Managed and queried datasets such as the CK+ facial emotion dataset, customer reviews big data, wearable device user interaction logs, and prototype testing data for UX research, aiding in product design optimization and decision-making through A/B testing.

  • PowerBI

    Power BI

    Built interactive dashboards visualizing sales trends, market insights, customer sentiments, and product performance, streamlining data-driven decision-making processes and significantly reducing manual analysis time.

Testimonials

  • Emily

    Emily R. | Head of E-commerce Strategy

    "Working with Jennifer was a great experience. She has a strong ability to translate complex data into meaningful insights, helping improve both product development and customer experience. Her knowledge of AI, machine learning, and user behavior made her a key contributor to our research team. She is thoughtful, collaborative, and always eager to tackle new challenges."

  • Jason Lou

    Jason L. | Senior Data Scientist

    "Jennifer is an exceptional data analyst and researcher. She approaches every project with curiosity and precision, ensuring that data-driven decisions are well-founded. Her ability to combine psychology and data science is truly impressive, making her an invaluable asset in behavioral research. She is a dedicated professional with a strong passion for solving complex problems."

Resume

Education

  1. University of Amsterdam (UvA) | MSc Data Science

    2024 — Now

    Relevant Coursework: Big Data analysis, Behavioural Data Science Toolbox, Deep Learning in Python, Psychometrics.

  2. The London School of Economics (LSE)| MSc Social and Cultural Psychology (GPA: 3.85/4.00)

    2021 — 2022

    Relevant Coursework: Consumer Psychology for Sustainability, Qualitative and Quantitative Research Method, Contemporary Social and Cultural Psychology, Organizations, Groups and Identity.

  3. Durham University | BSc Psychology (GPA: 3.70/4.00)

    2017 — 2020

    Relevant Coursework: Emotions and Social Perception, Abnormal Psychology, Cognitive Psychology, Biological Psychology, Psychology of Illness, the Research Method of Psychology.

Experience

  1. Senior UX Researcher

    2023 — 2024

    Conducted full-cycle analysis of infant product lines using machine learning to extract product and user insights, supporting data-driven product development. Automated usability testing and reporting pipelines, streamlining testing processes and enhancing decision-making efficiency.

  2. User Researcher

    2022 — 2023

    NDeveloped a deep learning-based chatbot to enhance customer service efficiency and improve user interactions. Led A/B testing and user segmentation analysis, optimizing product design, marketing strategies, and business decision-making through data-driven insights.

  3. Data Analyst

    2021 — 2022

    Developed predictive and statistical models to improve app performance and user retention in the mental health sector. Automated research processes and analyzed user data to support evidence-based feature development and proactive interventions.

My skills

  • Business Intelligence & User Research
    70%
  • Research & Technical Documentation
    55%
  • Statistical Modeling
    80%
  • Artificial Intelligence & Automation
    45%