Blake Rover
New York,USA
Summary
Dynamic research professional with experience at BBC Studios and the University of Cambridge, specializing in data analysis and machine learning. Proven ability to enhance audience engagement metrics and develop predictive models. Skilled in Python programming and UX design, with a strong aptitude for collaborative problem-solving and innovative thinking.
Overview
2
2
years of professional experience
Work History
Research Assistant Intern
BBC Studios
New York, USA
06.2023 - 06.2024
- Conducted data research and content analytics for multiple campaigns; assisted in evaluating audience engagement through statistical tools and AI-based audience insight models.
- Contributed to a cross-departmental team developing new metrics for predictive audience interest forecasting.
Researcher in Psychiatry, Neuroscience, and Technology
University of Cambridge
06.2022 - 09.2022
- Explored machine learning applications in digital mental health, using signal processing and algorithmic modeling to analyze behavioral and biometric data.
- Contributed to research on adaptive systems for early detection of cognitive decline.
Education
Master of Science - Emerging Technologies – User Experience & Design
New York University, Tandon School of Engineering
05.2025
Bachelor of Arts - Mind and Brain Studies
Bard College at Simon’s Rock
05.2023
Skills
- Python programming
- Data analysis and visualization
- Machine learning techniques
- UX research and design
- Cloud computing (AWS)
Projects
Wayfinder AI, AI Productivity & Financial Decision Support System, Developed a Python-based AI application using AWS Bedrock and YFinance to generate predictive insights on market trends and automate research workflows. Integrated NLP-driven task orchestration and performance metrics for workplace optimization. Financial Forecasting Suite, Machine Learning & Market Analysis, Built layered predictive modules (Python, Pandas, scikit-learn) to forecast equity price movement with 70–80% confidence using news sentiment and market data APIs. Designed a data visualization dashboard for confidence scoring and portfolio simulation. Neuro-Interactive Systems, BCI & Affective Computing Project, Designed EEG-integrated emotion recognition systems using Muse SDK and face-api.js to explore human-AI interaction and behavioral inference. Applied multimodal data fusion to improve model interpretability and user engagement.
Hobbies and Interests
- AI for Financial Systems
- Data-Driven UX Design
- Predictive Modeling
- Investment Research Automation
Timeline
Research Assistant Intern
BBC Studios
06.2023 - 06.2024
Researcher in Psychiatry, Neuroscience, and Technology
University of Cambridge
06.2022 - 09.2022
Master of Science - Emerging Technologies – User Experience & Design
New York University, Tandon School of Engineering
Bachelor of Arts - Mind and Brain Studies
Bard College at Simon’s Rock