Saloni Ajmera
About Saloni Ajmera
Saloni Ajmera is the Lead Data Quality Engineer specializing in Gen AI and Machine Learning at Coupa Software, with extensive experience in data analysis and predictive modeling.
Title
Saloni Ajmera currently holds the position of Lead Data Quality Engineer specializing in Gen AI and Machine Learning at Coupa Software. She began this role in 2023.
Employment at Coupa Software
Saloni Ajmera has been with Coupa Software since 2018. She initially joined as a Data Quality Engineer focusing on Machine Learning and progressed to the role of Senior Data Quality Engineer in 2021. As of 2023, she has taken on the role of Lead Data Quality Engineer in Gen AI and Machine Learning, working on-site in San Mateo, California.
Previous Experience
Prior to joining Coupa Software, Saloni Ajmera worked at Apple as a Data Analyst and Software Integration Specialist for Apple Maps from 2017 to 2018. She has also held various short-term positions, including Data Analyst at Local Insights, Sr. Business Data Analyst at Bank of the West, and Data Specialist in Research and Machine Intelligence at Google. Additionally, she has interned at Pluto7 and volunteered as a Data Analyst at the Nasdaq Entrepreneurial Center.
Education and Expertise
Saloni Ajmera has a strong educational background in data science and IT management. She completed her Master's of Science in IT Management (Business Data Analytics) at Golden Gate University from 2015 to 2016 and studied Data Science at General Assembly in 2017. She holds a Bachelor's degree in Computer Science and Engineering from Medicaps Institute of Technology and Management, earned from 2008 to 2012.
Technical Skills and Tools
Saloni Ajmera is skilled in using a variety of software and analytical tools for developing statistical models. She is proficient in scripting with Python to automate manual processes and uses BI tools like Tableau, Jupyter Notebook, and QGIS to create dashboards. Her expertise includes creating predictive models with techniques such as forward and backward regression and effectively visualizing and communicating data.