Background

I am a passionate Data Scientist with over 10 years of experience in building end-to-end Artificial Intelligence products in the Telecom, Healthcare, and Financial Services industries. With robust technical and leadership skills, I have applied AI to various business situations, helping organizations adopt data-driven solutions. Over the past decade, I have applied various machine learning methods such as classification, regression, time series analysis, and clustering, leveraging strong domain knowledge. I have deployed and maintained models in production on both Cloud and on-premise systems. I have collaborated with product managers, stakeholders, and business owners to effectively implement AI products across business units. I have worked with structured, semi-structured, and unstructured data, including near real-time and batch processing of data. I have also mentored Data Scientists and Machine Learning Engineers and helped them in their careers.

Motivation

As a seasoned Data Scientist, my motivation for joining the mentoring program stems from my desire to give back to the data science community, my thirst for continuous learning, and my enthusiasm for connecting with professionals from diverse backgrounds. I am deeply passionate about supporting young and aspiring data scientists. I believe that the field of data science is vast and constantly evolving, making it challenging for newcomers to navigate. By sharing my experiences and insights, I hope to provide guidance and support to those who are just embarking on their journey in this field. While I aim to impart knowledge, I also look forward to learning from the fresh perspectives and innovative ideas that mentees often bring to the table. This continuous learning process is what keeps me motivated and helps me stay abreast of the latest trends and technologies in data science. I am excited about the potential impact I can make and eagerly look forward to the journey ahead.

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• statistical and data modelling
• data analytics
• MLOps
• big data
• data visualisation
• natural language processing (NLP)
• problem solving
• statistics and mathematics
• data management
• causality and explainability
• time series analysis
• data mining
• computer vision
• cloud computing
• leadership
• high-performance computing
• engineering
• version control