Aayush Gupta

Data Scientist

Bengaluru, Karnataka, India7 yrs 7 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Led a team to improve underwriting model performance.
Transformed payment routing, saving millions.
Developed innovative solutions in NLP and Computer Vision.

Stackforce AI infers this person is a Data Scientist with expertise in Fintech and advanced machine learning solutions.

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Skills

Core Skills

Machine Learning

Other Skills

AWS SageMakerData Infrastructure ManagementSQLComputer VisionNeural NetworksNatural Language ProcessingGoogle CloudAnalytical SkillsStatistical Data AnalysisStatistical ModelingXGBoostRandom ForestPandas (Software)NumPyData Visualization

About

As a Data Scientist , I apply my Machine Learning skills to build and deploy scalable and robust machine learning solutions for the fintech industry. I have over 5 years of experience in data science and machine learning, solving complex business problems using ML and cloud technologies. Previously, I worked as a Staff Data Scientist at Simpl, where I led a team of two data scientists in developing and deploying an underwriting machine learning model that improved approval rates by 5% and reduced delinquency by 2%. I also managed data infrastructure, including data pipelines and databases, to ensure data quality and accessibility for the underwriting team. At Razorpay, I designed and implemented an end-to-end solution for smart routing of payments, saving millions of dollars and increasing the success rate by 4-6%. I published a paper at IEEE Conference for the same. I hold a Master of Science in Mathematics from BITS Pilani and a PG Diploma in Machine Learning and AI from IIIT Bangalore. I am passionate about learning new technologies and tools, and I have obtained multiple certifications, including Google Cloud Platform Associate Cloud Engineer and Technical Intern from Visakhapatnam Steel Plant. I have also been an integral part of the Learning and Development Committee to train the newly joined campus hires joining as Machine Learning Engineers. My goal is to leverage my skills and experience to deliver value and innovation for the fintech sector.

Experience

7 yrs 7 mos

Total Experience

1 yr 7 mos

Average Tenure

1 yr 1 mo

Current Experience

Zomato

Senior Data Scientist

Apr 2025 – Present · 1 yr 1 mo · Bengaluru, Karnataka, India · On-site

Mpower financing

Sr Data Scientist

Dec 2023 – Feb 2025 · 1 yr 2 mos · Bengaluru, Karnataka, India · Hybrid

Simpl

Staff Data Scientist

Aug 2022 – Nov 2023 · 1 yr 3 mos · Bangalore Urban, Karnataka, India

Led a team of two data scientists in developing and deploying an underwriting machine learning model that improved approval rates by 5% and reduced delinquency by 2%.
Proactively identified and resolved technical issues related to data collection, preparation, and analysis, ensuring accurate and reliable results. Optimized SQL queries to extract raw data, leading to a 40% decrease in model training time from 10 to 6 hours.
Managed data infrastructure, including data pipelines and databases, to ensure data quality and accessibility for the underwriting team. Conducted A/B testing to evaluate the new model’s performance

Machine LearningAWS SageMaker

Razorpay

Data Scientist

Nov 2020 – Aug 2022 · 1 yr 9 mos · Bangalore Urban, Karnataka, India

• Smart Routing of Payments: Transformed the existing rule-based system to a scalable ML system that intelligently handles payment transactions and routes payments through the best terminal. Designed and implemented the end-to-end solution, saving millions of dollars and increasing the success rate by 4-6%. Published the paper at IEEE Conference for the same

Machine LearningSQL

Quantiphi, inc.

Machine Learning Engineer

Jul 2018 – Nov 2020 · 2 yrs 4 mos · Mumbai, Maharashtra, India

Automated Call Summarization (Natural Language Processing):
Built the pipeline for automated Call Summarization involving Google’s Speech to Text API and Bert-based models to generate extractive and abstractive summaries for Agents and Customers. Improved the overall execution time by 50% by drastically reducing manual efforts.
Crew Assisted Monitoring System & Trespasser Detection System (Computer Vision):
Built a Video-Analytics solution capable of detecting and classifying objects (flags, signals, tracks, plates, trespassers) from the real-time video feed through the train’s front camera. This solution assisted the driver in better decision-making and enabled Advanced Analytics based on geometrical data points.
Automatic Invoice Generation (Audio Analysis):
Developed an end-to-end solution that took real-time verbal orders and returned structured outputs as invoices, by integrating Google Cloud Speech to Text API with a custom-trained Named Entity Recognition NER model.

Computer VisionNeural NetworksMachine Learning