---
title: "Pratik Kotkar - Principal Data Scientist in Bengaluru | Tal"
description: "Meet Pratik Kotkar, Principal Data Scientist @ bicycle.ai | Engineer | AI based in Bengaluru. AI stack includes claude, cursor, and deepseek."
image: "https://tal.club/meet/pratik-kotkar/share-image"
---

# Pratik Kotkar on Tal

## Headline

Principal Data Scientist @ bicycle\.ai \| Engineer \| AI

## About

Leveraging AI to solve business data science challenges\.

## Location

Bengaluru

## AI stack

claude

cursor

deepseek

kimi

openai

claudecode

## Work experience

Principal Data Scientist at Bicycle AI, Feb 2026 \- Present · 7 mos, Bengaluru, Building AI agents for ML problems

Lead Data Scientist at twid, Aug 2024 \- Feb 2026 · 1 yr 7 mos, Hybrid, Built E2E ML pipeline from model design to development and deployment\. Used Airflow, Clickhouse db as a part of deployment\. Processed data for about 150M customers Next challenge incoming is to reduce runtime responses of models for further operations

Senior Data Scientist at twid, Jun 2023 \- Aug 2024 · 1 yr 3 mos, Bengaluru, Karnataka, India, Working on Customer Eligibility Score using supervised machine learning techniques to improve current manual operations scenarios and rule based systems for customer eligibility identification\. Building a customer merchant affinity engine to optimise the discounts and improve GMV and Success Rates

Personal goal pursuit at Career Break, Apr 2023 \- May 2023 · 2 mos, Bengaluru, Karnataka, Studied about Machine Learning techniques in generative AI , read research papers and implementation of RAGs and LLMs , created an app for automated content generation and moderation using LLMs and performed end to end implementation of a ML model from data collection to consumption using airflow, kubeflow, docker , AWS Sagemaker etc

Senior Data Scientist at Niyo Solutions Inc\., Oct 2022 \- Mar 2023 · 6 mos, Lending Propensity Model : Model built to identify the high propensity customers to buy loans from the bank\. An ensemble method was used to determine the probability of customers most likely to consider buying a loan AWS sagemaker was used for deployment of the model , ML pipeline was setup as API endpoints needed to be exposed This model helped filtering out the customers with high propensity which resulted in 20% improved disbursement rate Model has a Recall of 79\.5% which is pretty good for the initial level of data \(less samples of disbursement available\)\.Building a user profile with the help of multiple data sources to create a scoring system to define the approval likelihood in case the user opts to buy the loan from the bank\. Marketing Source Mix Optimization : Marketing team needed a direction to spend the budget wisely in order to maximize the output keeping the KPIs such as D7 Load, Activation etc in control Built a model using Linear Programming method \(opensolver\) which gave us the right split of users to be acquired from each source such as Google,FB, Affiliate etc with CAC and budget distributed accordingly across sources\. Changes made due to this model helped us increase 5\-7% of user base Week on Week and eliminate the non performing sources beforehand saving about $20k\-30k /month and spend it in the appropriate sources\.

Data Scientist at Niyo Solutions Inc\., Jan 2022 \- Oct 2022 · 10 mos, Bengaluru, Karnataka, India, VKYC Demand Filtering Algorithm : Created a demand filtering algorithm for choosing the best customers for the enablement of VKYC option\. Based on onboarding data, identified customers with the highest propensity of getting a banker’s approval\. Used XGBoost for feature engineering and selection , and generated rules for segments to create a filtering criteria for customers on the go and deployed it to production\. We’ve seen an improvement from 20% to 24% within first week of deployment, upcoming weeks to show more positive results to beat the market benchmark of 60%

Business Analyst \(Data Science\) at PharmEasy, Nov 2020 \- Jan 2022 · 1 yr 3 mos, Bengaluru, Karnataka, India

Software Developer at Hansen Technologies, Jul 2018 \- Nov 2020 · 2 y 4 mo, Pune

Intern at Nidhi investment, Dec 2017 \- Apr 2018 · 4 mo, Pune

## Education

Bachelor of Engineering, Computer Science, Maharashtra Institute of Technology

[View the original profile](https://tal.club/meet/pratik-kotkar)

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