Mahammad Ansari
About Mahammad Ansari
Mahammad Ansari is a Lead Data Scientist with extensive experience in data analysis and predictive modeling. He has worked in various roles across multiple companies, including Mphasis, Alcatel Lucent Managed Services, and Aspire Systems, and possesses strong skills in data visualization, database management, and natural language processing.
Current Role at Aspire Systems
Mahammad Ansari serves as the Lead Data Scientist at Aspire Systems, a position he has held since 2021. In this role, he applies his expertise in data science to develop predictive models and conduct exploratory data analysis (EDA). His work focuses on deriving actionable business insights from complex datasets, enhancing decision-making processes within the organization.
Previous Experience in Data Science
Prior to his current role, Mahammad Ansari worked as a Senior Data Scientist from 2015 to 2021. His responsibilities included utilizing advanced data analysis techniques and developing automation solutions. He specialized in Rule Based Automation using Python, contributing to efficiency improvements in data processing tasks.
Background in Engineering and Data Management
Mahammad began his career as a Network Engineer at Mphasis from 2007 to 2010. He then transitioned to Alcatel Lucent Managed Services, where he worked as a Senior Engineer from 2010 to 2014. His experience includes application support and analysis, which laid the groundwork for his later roles in data science. He also worked at UST as an Associate Infrastructure Analyst from 2014 to 2015.
Education and Technical Skills
Mahammad Ansari earned his Bachelor's degree in Computer Science from West Bengal University of Technology, Kolkata, from 2003 to 2007. He possesses strong technical skills in SQL and NoSQL databases, enabling him to manage data effectively. Additionally, he is skilled in using Tableau for data visualization, which aids in presenting complex data in an understandable format.
Expertise in Natural Language Processing
Mahammad has developed expertise in Text Mining and Text Analytics, with a focus on Sentiment Analysis and Text Classification through Natural Language Processing (NLP). This specialization allows him to extract meaningful insights from textual data, which is increasingly valuable in various business applications.