Collaborate with clients and internal teams to define, design, and deliver data-driven solutions for business problems using leading edge and open source tools such as Python, R and Tensorflow, combined with AI Application suits.
Perform exploratory data analysis (EDA), statistical modeling, and hypothesis testing to uncover insights.
Design and build machine learning models (classification, regression, clustering, recommendation systems, time series forecasting, NLP, computer vision).
Develop and deploy end-to-end ML pipelines for training, validation, deployment, and monitoring.
Apply feature engineering, dimensionality reduction, and optimization techniques to improve model accuracy and efficiency.
Work on advanced analytics projects including churn prediction, profiling, and recommendation engines.
Deploy ML models into production environments using Flask, FastAPI, Docker, MLflow, or cloud ML services (AWS, Azure, GCP).
Monitor post-deployment model performance and implement re-training strategies.
Create interactive dashboards and reports using Power BI, Tableau, or Python visualization libraries to communicate insights.
Stay updated with state-of-the-art ML/AI advancements and proactively bring innovative approaches to client projects.
Evaluating modeling results and document workflows and present complex findings in a simple, interpretable way to technical and non-technical stakeholders.
