Narpat R Kalwaniya

Frontend Engineer

Nagaur, Rajasthan, India7 yrs 7 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in React and JavaScript frameworks.
Proven track record in data-driven decision making.
Strong leadership in cross-functional team collaborations.

Stackforce AI infers this person is a Frontend Developer with expertise in Healthcare and Data Analytics.

Contact

Skills

Core Skills

ReactJavascript FrameworksData AnalysisStatistical Modeling

Other Skills

A/B TestingAdobe IllustratorAdobe PhotoshopAgile DevelopmentAgile MethodologiesAmazon Web Services (AWS)AnalyticsAngularJSApplication Programming Interfaces (API)Artificial Intelligence (AI)Attention to DetailBack-End Web DevelopmentBootstrap (Framework)CC++

About

At Tiger Analytics, our team has successfully supported a premier Pharmaceutical Business by developing a Marketing Mix application using React TypeScript. This endeavor leverages my expertise in JavaScript frameworks and DOM to create intuitive, responsive user interfaces enhanced by Material UI and Recharts for data visualization. Holding a Bachelor of Technology from IIT Kharagpur, my foundation in engineering principles complements my professional journey. Our collective achievements reflect a dedication to building scalable solutions and a penchant for transforming data insights into actionable strategies, bolstered by a robust understanding of analytics and user experience design.

Experience

7 yrs 7 mos

Total Experience

1 yr 3 mos

Average Tenure

3 yrs 11 mos

Current Experience

Tiger analytics

3 roles

Lead Frontend Developer

Jan 2025 – Present · 1 yr 5 mos

Supporting a Marketing Mix application for a leading Pharmaceutical Business developed in React Typescript.

React TypeScriptJavaScript frameworksDOMMaterial UIRechartsReact+1

Senior Engineer

Promoted

Jul 2023 – Jan 2025 · 1 yr 6 mos

Project 1:
In collaboration with a team of Consultants, Data Scientists, DevOps Engineers, and Developers, contributed towards a successful launch of a marketing mix application using React TypeScript
with Material UI for a responsive, visually appealing interface. Implemented React Query for client side caching and used Redux to manage complex state and API interactions effectively. To offer visualizations for data insights, incorporated customized trend, bar, stack and pie charts using Recharts. Also incorporated user-friendly features like a date picker, file upload, and download functionalities.
Project 2:
Designed and developed OCR, Translate, and Image Generator applications with features like file handling and user feedback (like, comment), optimized workflows using S3 presigned URLs, integrated WebSocket communication, and improved prop flow with Context API for a GenAI application

React TypeScriptMaterial UIReact QueryReduxRechartsWebSocket+3

Data Analyst

Jul 2022 – Jul 2023 · 1 yr

Worked on estimation of Conversion Likelihood of Opportunities with different product/market/consumption segments & geographies using statistical tests, EDA, and feature engineering, building a logistic regression model with accuracy improved from ~0.85 to ~0.91 with VIF selection

Statistical testsEDAFeature engineeringLogistic regressionData AnalysisStatistical Modeling

Episource

Data Science Intern

Jan 2022 – Jul 2022 · 6 mos

Accustomed to medical coding and leveraged data analytics tools to adjust the penalty risk associated with US Health Insurance Business; Programmed multiple algorithms in SQL & pandas to process medical claims, codes, and pharmacy data retrospectively to flag issue codes

SQLPandasData Analysis

Curl

Data Science Intern

May 2021 – Sep 2021 · 4 mos

Worked on enhancement of Product Strategies of gaming businesses using Descriptive and Predictive Data Analysis. Programmed python functions to expedite the process of drawing personalized game/region/proxy/genre specific insights for better user experience. Also performed univariate and multivariate EDA; engineered new features; experimented on different feature importance techniques such as SHAP, SelectKBest, RFECV etc.
Contributed to a project that aims the automation and reorganization of data extracted from scanned documents according to requirements. Got a chance to explored and experiment on the functionalities of pdfplumber, pdfminer, paddleocr, tesseract, easyocr on documents of different formats. Finally built an algorithm to automate the reorganisation of default outputs from pdfplumber and easyocr into word, line, para and page levels.

PythonDescriptive Data AnalysisPredictive Data AnalysisData Analysis

Resurgentagric, bengaluru

Multi-domain Intern

Dec 2020 – May 2021 · 5 mos

Written CommunicationCommunication

Agricultural engineering society

3 roles

President

Promoted

Jul 2020 – Jul 2021 · 1 yr

Representative of 300+ students of Agricultural and Food Engineering Department to function as a key link between the scholars and faculty; to work in coordination with administration to execute departmental activities
Responsible to superintend the conduction of Prakriti 2021, the largest agri and food innovation fest of India

General Secretary

Promoted

Apr 2019 – Jul 2020 · 1 yr 3 mos

Secretary

Aug 2018 – Jul 2020 · 1 yr 11 mos

Rajasthan cultural association

3 roles

Governor

Jul 2020 – Jul 2021 · 1 yr

Responsible for directing the conduction of a number of online/offline events aiming culture and rituals spread
Overseeing the management and development of a team of 35 members by conducting self-growth sessions

Head Of Finance

Promoted

Apr 2019 – Jul 2020 · 1 yr 3 mos

Sponsorship and Design Subhead

Aug 2018 – Jul 2020 · 1 yr 11 mos

Written CommunicationCommunication

Sitel group

Business Analyst

Jun 2020 – Jul 2021 · 1 yr 1 mo

Written CommunicationCommunication

Vegamx inc.

Data Analytics Intern

May 2019 – Jul 2019 · 2 mos · IIT Kharagpur

Developed and optimized a Corn Yield Prediction Model using the Corn Yield Data of USA for the years 1980-2018
Explored several feature scaling/standardization and hypertuning techniques such as GridSearchCV and RandomSearchCV
Compiled Linear Regression, Random forest and RNN model which resulted into the prediction with a significantly low MAE

Written CommunicationCommunication