Responsibilities
- ✔️ Analyze and interpret complex datasets to build predictive, prescriptive, and automated insights.
- ✔️ Apply advanced ML techniques such as NLP, LLM fine‑tuning, deep learning, and computer vision.
- ✔️ Build statistical models and AI‑driven solutions to solve business challenges.
- ✔️ Perform exploratory data analysis (EDA) using Python, R, or SQL.
- ✔️ Develop prototypes and proof‑of‑concept AI models.
- ✔️ Work with business leaders to define data‑driven strategies and KPIs.
- ✔️ Research bleeding‑edge AI trends and evaluate opportunities for adoption.
- ✔️ Build and maintain datasets required for training and inference.
- ✔️ Visualize insights through dashboards and storytelling tools.
- ✔️ Implement feature engineering, data transformations, and ML enhancements.
- ✔️ Validate model accuracy using cross‑validation and advanced metrics.
- ✔️ Document methodologies, findings, and recommendations.
- ✔️ Present insights to leadership in a clear and data‑driven manner.
- ✔️ Work closely with ML Engineers to productize models.
- ✔️ Ensure AI models follow ethical and regulatory standards.
- ✔️ Develop predictive analytics for forecasting, churn analysis, and segmentation.
- ✔️ Participate in continuous improvement of AI frameworks.
- ✔️ Conduct statistical experiments and hypothesis testing.
- ✔️ Mentor analysts and junior scientists on AI and ML concepts.
- ✔️ Support strategic planning for long‑term AI roadmap initiatives.
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