How to Become a AI Analytics Strategist

Build a classification model (e.g., XGBoost) on a telecom or SaaS dataset to predict churn probability. Create a dashboard to visualize risk scores for customer segments and define rules for automated retention campaigns (e.g., trigger a discount offer for high-risk users).

Use the OpenAI API to generate multiple ad copy or email subject line variants. Build a simple system to track simulated or real A/B test performance (click-through rates). Use the results to fine-tune the prompt or select the best-performing model parameters, creating a feedback loop.

Develop a pipeline that scrapes social media posts or reviews for a brand, uses a pre-trained NLP model (like from HuggingFace) for sentiment analysis, and applies topic modeling (LDA or BERTopic) to identify key discussion themes. Output a daily report summarizing sentiment trends and emerging topics.

Using a dataset of user journeys with multiple touchpoints (e.g., ad clicks, email opens, website visits) and a final conversion, implement a probabilistic model (like a Markov chain or Shapley value approximation) to assign credit to each channel. Build a visualization comparing the model's output to simplistic models like last-click attribution.