I'm
Sanskriti Rathaur
About me
I’m currently working in a data-driven role where I actively use Python, SQL, and cloud technologies to build, analyze, and deploy scalable data solutions.
My day-to-day work involves: Developing Python scripts for data processing, automation, and analysis.
Working with LLMs for intelligent data workflows and experimentation.
Using AWS services for cloud-based analytics and integrations.
Building and maintaining data pipelines using Alteryx and Snowflake.
Writing optimized SQL queries for large-scale datasets.
Supporting model building and validation for analytical use cases.
Collaborating across teams using Jira and ServiceNow for task tracking and incident management.
I enjoy working at the intersection of analytics, cloud, and AI, turning complex requirements into practical, business-ready solutions.
I value clean logic, reproducible workflows, and clear communication with both technical and non-technical stakeholders.
Currently focused on strengthening my expertise in LLM-powered analytics, cloud-native data platforms, and end-to-end data solutions.
My Skills
Experience
- ‣ My day-to-day work involves: Developing Python scripts for data processing, automation, and analysis.
- ‣ Working with LLMs for intelligent data workflows and experimentation.
- ‣ Using AWS services for cloud-based analytics and integrations.
- ‣ Building and maintaining data pipelines using Alteryx and Snowflake.
- ‣ Writing optimized SQL queries for large-scale datasets.
- ‣ Supporting model building and validation for analytical use cases.
- ‣ Collaborating across teams using Jira and ServiceNow for task tracking and incident management.
- ‣ Implemented customer segmentation using clustering and feature engineering on online retail data, boosting marketing precision and targeting efficiency by 95%.
- ‣ Engineered a sophisticated recommendation algorithm with ML models in Python that realized in a notable 15% growth in average order values, positively impacting customer purchasing behavior and satisfaction rates.
- ‣ Boosted decision-making and business performance by 90% using Python for statistical analysis, demand forecasting, and predictive modeling.
My Projects
