Sumit Singhal

Data Scientist

Bengaluru, Karnataka, India3 yrs 9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Led projects saving ₹1 million monthly at Slice.
Developed ML framework reducing flight delays by 14 minutes.
Created award-winning AI chatbot at hackathon.

Stackforce AI infers this person is a Data Scientist with expertise in Fintech and Machine Learning.

Contact

Skills

Core Skills

Computer VisionDeep LearningGenerative AiNatural Language Processing (nlp)Data ModelingBayesian OptimizationMachine Learning

Other Skills

Python (Programming Language)Statistical ModelingNaive BayesHeatmapData VisualizationBayesian statisticsMongoDBREST APIsTransfer LearningNeural NetworksLong Short-term Memory (LSTM)Audio ProcessingLean Six SigmaControl ChartsRoot Cause Analysis

About

I have 2+ years of experience in data science through jobs and internships. I graduated from IIT Kanpur and joined Slice as a data scientist, and I have been working there for the past 1.5 years. At Slice, I worked in two verticals. In the first vertical, I was in the machine learning pod. I spearheaded facial features and spoof face detection models, saving Rs 1 million monthly. I enhanced the user experience by generating avatars and interactive QR codes using generative AI. Collaborating on a prize-winning customer support AI chatbot secured Rs. 1.5 lakh at a hackathon. Under the second vertical, I was in the collections team. I managed defaulting user data and crafting and implementing sophisticated debt collection risk models by analyzing 80 key features over 6 months. My strategic optimization of user allocation among tele-calling agents resulted in an impressive 18% increase in late payment collections. As a data science intern at ITC Limited, I performed statistical modeling on machine breakdown and production data to enhance unit productivity. In my one-year IIT Kanpur research, I authored a paper on machine learning, in which I developed an ML framework to reduce flight delays by 14 minutes. College projects include predicting audio events with semi-supervised learning and forecasting car insurance claims using classical ML techniques.

Experience

3 yrs 9 mos

Total Experience

1 yr 3 mos

Average Tenure

1 yr 3 mos

Current Experience

Myntra

2 roles

Senior Data Scientist

Apr 2026 – Present · 2 mos · On-site

Data Science Engineer

Feb 2025 – Mar 2026 · 1 yr 1 mo · On-site

Acko

Data Scientist

Jan 2024 – Feb 2025 · 1 yr 1 mo · Bengaluru, Karnataka, India · On-site

Slice

2 roles

Data Scientist

Promoted

May 2023 – Nov 2023 · 6 mos · Bengaluru, Karnataka, India · On-site

I successfully led key projects in Computer Vision, achieving over ₹1M in monthly savings through a custom user onboarding pipeline and improving face and eye detection with Google ML Kit. In Deep Learning, I developed a robust liveliness detection model and optimized hyperparameters with precision. My expertise extended to Generative AI, where I created realistic avatars and implemented advanced models for QR code generation utilizing Stable Diffusion Models and Control Nets. In Algorithm-design, I developed an even user-agent distribution system and improved collections by 24% through language optimization. Data Engineering efforts included pipeline enhancement and RESTful API architecture. Additionally, my work in Natural Language Processing to create customer support AI led to enhanced chatbot resilience and a hackathon-winning chatbot creation.

Python (Programming Language)Deep LearningComputer Vision

Software Engineer

Jun 2022 – May 2023 · 11 mos · Bengaluru, Karnataka, India · On-site

Itc limited

Data Scientist

May 2021 – Jul 2021 · 2 mos · Munger, Bihar, India · On-site

During my tenure as a Techno Managerial Intern at ITC Limited, I delved into the realm of Industry 4.0, focusing on Real-Time Condition-Based Monitoring for machine KPIs, all under the banner of Six Sigma excellence.
My contributions included the identification of 9 crucial factors for machine breakdown, leading to the development of alert conditions using EMWA control charts. This was further augmented by a rigorous Root Cause Analysis conducted within a Six Sigma framework, resulting in the identification of 10 critical attributes that had been leading to false rejections.
The results of this endeavor were remarkable: a 21% increase in production, made possible by the implementation of a monitoring system across the machine's three KPIs through the utilization of Power BI and Python. Simultaneously, there was a 60% reduction in the overall rejection rate within the factory, accompanied by the successful execution of two major projects instead of one as originally planned.

Bayesian OptimizationStatistical Modeling

Indian institute of technology, kanpur

Optimized Flight Departure Time using Machine Learning and Bayesian Techniques

Jan 2021 – Jun 2022 · 1 yr 5 mos · Kanpur, Uttar Pradesh, India · Remote

As the sole first author of a 40-page research paper currently under review at Transportation Research Part C having impressive H-index of 164, I've showcased strong research and analytical skills. I developed a Bayesian ML framework with multiple loss functions that saved 1630 minutes, reducing delays for 83% of flights. I extracted crucial parameters from government datasets and identified 12 key factors affecting flight delays utilizing SHAP plots and WMA charts. Statistical analysis and machine learning techniques like Ridge regression, XG-Boost, ANN, and LightGBM were used to create a delay prediction pipeline with an impressive 84% F1 score. Furthermore, I leveraged Bayesian optimization for optimizing flight departure times to minimize journey delays. This research demonstrates a profound understanding of the subject matter and expertise in data analysis and machine learning.