Drive product impact by proposing and conducting quantitative research into key user behaviors and trends
Conduct in-depth analysis and build statistical models to identify trends and key drivers that inform important decisions made by the user.
Data analysis to identify common trends
Based on analysis, propose enhancements for automation pipelines.
Review the output of AI models to improve performance by identifying common usage gaps
Optimise AI model performance through effective prompt engineering techniques.
Establish automated model performance improvement pipelines through prompt engineering.
Responsible for generating, testing, evaluating, and curating high-quality, diverse, and representative data (including synthetic) for AI model development, training, and performance.
Analyse model performance by diving into user feedback data and product usage reports.
Suggest ways to improve product usage by specifically targeting each group of users and also feature.
Create a business analysis report weekly.
Define and monitor key metrics; investigate changes in metrics.
Driven to continuously learn and adapt.
Requirements
Bachelor's degree or above with a good academic background.
1-2 years of full-time work experience as an AI Analyst.
A highly resourceful individual who is looking to grow in the SaaS AI field.
Experience in Python (Pandas, Matplotlib, NumPy) is a must.
Experience in SQL is a must.
Experience with Prompt Engineering is a plus.
Familiarity with Classical ML Models (scikit-learn) and Deep Learning (Hugging Face, PyTorch) is a plus.
Experience with Data Engineering is a plus.
Employing test findings to do Statistical analysis and improve models.
Knowledge of common metrics for evaluation of ML models is a plus.
Tech Stack
Numpy
Pandas
Python
PyTorch
Scikit-Learn
SQL
Benefits
We offer market-leading compensation, based on the skills and aptitude of the candidate.