Ashok Kumar

Consultant

India5 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Achieved 96% accuracy in NLP ticket classification.
Reduced incidents by 35-40% through ML dashboard integration.
Designed automated solutions enhancing operational efficiency.

Stackforce AI infers this person is a skilled developer in Fintech with expertise in automation and data science.

Contact

Skills

Core Skills

PythonMachine LearningData VisualizationData Analysis

Other Skills

BMC Control-MC++CSSDeep LearningDjangoFlaskHTMLHadoopJavaScriptNatural Language Processing (NLP)PandaPentahoPublic SpeakingQliksenseREST APIs

About

Developer with expertise in automation, machine learning, and data visualization. Skilled in Python, shell scripting, and Hadoop for efficient data handling. Developed NLP models with 96% accuracy for ticket classification and integrated ML outputs into Qliksense dashboards, reducing incidents by 35-40%. Proven in designing automated solutions and dashboards to enhance operational efficiency and streamline processes. Hands-on experience with Flask in personal projects. Enthusiastically seeking new opportunities in Python and data science to leverage my skills and drive innovation.

Experience

Hsbc

3 roles

Consultant Specialist

Aug 2025 – Present · 7 mos

Senior Software Engineer

Promoted

Apr 2021 – Aug 2025 · 4 yrs 4 mos

As a Software Developer at HSBC, I developed automated shell scripting solutions to streamline data retrieval and processing on production servers. I designed and implemented projects using Pentaho and shell scripting to dynamically generate new business fields. I leveraged Hadoop Distributed File System (HDFS) for efficient storage and processing of large structured and unstructured data. Collaborating with the team, I utilized Python and shell scripting to eliminate manual tasks, ensuring smooth operation of critical processes.
Furthermore, I developed NLP-based machine learning models using Python libraries such as NLTK and Gensim for ticket classification, achieving over 96% accuracy. I integrated ML model outputs into Qliksense dashboards, significantly enhancing data quality for stakeholders and resulting in a 35-40% reduction in incidents and better business decisions. Additionally, I created a Python model to track ticket resolution time, leading to more accurate MTTR calculations and improved resolution times. I also designed versatile Qliksense dashboards that integrated business logic and handled extensive datasets, providing actionable insights and optimizing VMs, thereby enhancing operational efficiency.

Shell ScriptingPentahoHadoopPythonNatural Language Processing (NLP)Qliksense+1