Senior Data Scientist with 8years of experience in transforming data into strategic assets, enabling industry leaders across Technology, BFSI, CPG to make informed business decisions through Advanced Analytics, Machine Learning (ML) , Deep Learning (DL) and Artificial Intelligence (AI). Proficient in designing and implementing end-to-end modeling pipelines using Python, SQL, and PySpark in cloud environments in AWS SageMaker. Currently developing products in Amazon DSP helping advertisers target valuable customers in a privacy-centric world. I have previously worked for Wells Fargo, one of the Big Four Banks in United States and also have consultancy experience with Fortune 100 clients. My journey as a Data Science Mentor so far: Currently I am volunteering in Amazon Future Engineer Initiative for nearly 2 years. Here I help and guide Women from underprivileged parts of the society, pursuing STEM to build their profile, prepare for Tech Industry based roles in 1-1 mentorship. I started to develop my passion in mentoring through my early days of Mu Sigma, followed by 2years of experience as Data Science Mentor at Springboard(1-1 mentorship), 1year of experience in Machine Learning and Python Instructor in classroom teaching with Data Is Good. I believe mentoring is a two way road. I am fortunate to have good mentors and mentees through out my career which helped me shape who I am. I learned from my mentees as much as I have learned from my mentors. In short term, I want to gather as much as experience in this field to help myself as well as others to adapt to the fast changing world of Data Science and AI ML. In long term, I want to be able to pursue this full time and have enough resources to kick off my very own non profit organisation to help more and more people across the underprivileged societies to pursue Tech as a Career. My motto is to ”Teach them how to fish and you help them for a lifetime”. Connect with me at https://topmate.io/suranjana_sarkar for more on my experience and any guidance on AI ML career in general.