Pratik Ratadiya

CEO

Jersey City, New Jersey, United States5 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led product development at Narravance with significant revenue growth.
Published research at multiple A+ conference venues.
Built strong community platforms with over 30,000 social media followers.

Stackforce AI infers this person is a SaaS and Aerospace professional with strong expertise in Machine Learning and Data Analysis.

Contact

pratadiya@ucsd.edu LinkedIn

Skills

Core Skills

Machine LearningProduct ManagementDeep LearningAnomaly DetectionData AnalysisMicroservicesKubernetes

Other Skills

AlgorithmsArtificial Intelligence (AI)BootstrapCC++Cascading Style Sheets (CSS)Computer VisionDjangoDockerFeature EngineeringGoHTMLJavaScriptMicrosoft OfficeNatural Language Processing

About

Hi! I am a founding member and the Head of Product at Narravance, where we try to identify signals from social media and the Internet that could impact the real world. Prior to this, I have worked with companies like Apple, NASA JPL, and JnJ on data science and machine learning projects, with my work getting published at multiple A+ conference venues. I am known to be a team player and a good communicator, who brings in a lot of ideas, energy, and technical expertise to the table. I am always ready to lead initiatives and build strong community platforms, as demonstrated through my experiences building multiple student communities in both India and the US, and now over 30,000 followers across social media.

Experience

Narravance

2 roles

Head of Product and Machine Learning

Promoted

Mar 2024 – Present · 2 yrs

Founding member of the company, where I have been leading technology and product direction. I came up with the idea, core algorithm, and managed the zero-to-one execution of our first product, ChatterFlow. I oversee our tech team of more than 6 engineers and analysts, work with design partners, and manage our external relationships with data vendors. In the last 18 months, we have grown to more than X million in revenue thanks to our intel team, and our technology has had a 99%+ uptime during this time to help the team with their research efforts.

Natural Language ProcessingMachine LearningPythonAlgorithmsData AnalysisProduct Management

Lead Machine Learning

Aug 2023 – Present · 2 yrs 7 mos

🤫🤫

Nasa jet propulsion laboratory

Visiting Researcher

Mar 2023 – Aug 2023 · 5 mos · Pasadena, California, United States · On-site

Part of the Mission Control Systems Deep Learning Technology (393K) group. Worked on improving anomaly detection for the power subsystems of Mars rover. Work accepted at AIAA SciTech 2024.

Anomaly DetectionDeep LearningData Analysis

Apple

Machine Learning Intern

Jun 2022 – Sep 2022 · 3 mos · Seattle, Washington, United States

Researched and implemented deep learning models for hate speech detection. Improved the F1 score of existing systems by 15%. Accomplished end-to-end project work: Managing data annotation, training models, deploying REST APIs, and integration with current pipelines.
Tools and technologies: PyTorch, HuggingFace, Flask, Scikit-learn

Machine LearningData Analysis

Uc san diego

2 roles

Graduate Student Researcher

Promoted

Jan 2022 – Jun 2023 · 1 yr 5 mos · San Diego, California, United States

Graduate Student Researcher for Prof. Dinesh Bharadia in the Wireless Communication Sensing and Networking (WCSNG) group. Worked on designing open-set classification and novelty detection methods from hardware fingerprinting. This module was a part of a the SCISRS project that has been funded by IARPA.
Graduate student member of the Computing for Social Good (CSG) lab under Prof. Mai ElSherief working on the application of AI to analyze social problems.

Machine LearningData Analysis

Graduate Teaching Assistant

Sep 2021 – Jun 2023 · 1 yr 9 mos · San Diego, California, United States

[Spring 23]: DSC 140B: Representation learning for Prof. Justin Eldridge. Grading + office hours + discussion forums
[Winter 23]: CSE 234: Data Systems for ML for Prof. Arun Kumar. Grading research paper reviews + office hours + exam proctoring. 100% approval
[Fall 22]: EDS 50: Intro to CASP for Belinda Zamacoma. Teaching lessons to 50+ freshmen selected in the Chancellor's Associates Scholars Program (CASP). 100% approval
[Spring 22]: DSC 190: Representation learning for Prof. Justin Eldridge. Class moderation + office hours + discussion forums. 100% approval
[Winter 22]: DSC 140A: Probability and ML for Prof. Jelena Bradic. Programming classes for 50+ students + grading + office hours. 100% approval
[Fall 21]: EDS 50: Intro to CASP for Prof. Dallawrence Dean. Teaching lessons to 15 freshmen selected in the Chancellor's Associates Scholars Program (CASP). 100% rated approval

Frontdoor, inc.

Tech Consultant

Oct 2020 – Apr 2021 · 6 mos · Pune, Maharashtra, India

Contracted to Frontdoor India as a Tech consultant while being staffed by vCreaTek consulting LLC. One of the first 5 members in the core development team of the Frontdoor Developer Portal (developer.frontdoorhome.com) Tasks included writing of microservices in Golang, collection validator scripts for MongoDB, JavaScript for frontend development, writing of OAS for API collections, and CI/CD pipelines.
Technologies used: Go, MongoDB, Swagger, Apigee, JavaScript, Bootstrap 4, CI/CD

MicroservicesJavaScript

Vcreatek consulting services pvt ltd

Data Scientist and Product Lead

Sep 2020 – Sep 2021 · 1 yr · Pune, Maharashtra, India

Researched and developed a volume forecasting model for the medical instruments department of Johnson & Johnson, reducing the MAE by 35%
Lead a team of 8 developers to build the MVP for Foshan, a product in the CTRM space. Streamlined the process for subsequent product development iterations.
Streamlined the training and onboarding process as the team leader of the Advanced Analytics Division.
Managed a group of 5 interns from IIT Bombay across two projects - Android app development for Foshan, and Tabular entailment using transformer NLP methods.

Data AnalysisMachine Learning

Indian institute of space science and technology

Summer Research Intern

May 2019 – Jul 2019 · 2 mos · Thiruvananthapuram, Kerala, India

Designed and developed a profanity detection system for the feedback modules of IIST under the guidance of Prof. Deepak Mishra. Achieved a top 1% score on the Kaggle comment toxicity detection challenge using a multihead attention ensemble. Work accepted at ICDM 2019 as a workshop paper.
Technologies used: Keras, Tensorflow, NLTK, Sklearn, Matplotlib, Pandas

Machine LearningData Analysis

Indian institute of technology, bombay

FOSSEE Summer Fellow

May 2018 – Jul 2018 · 2 mos · Mumbai, Maharashtra, India

Selected as one of the 60 FOSSEE Summer fellows from over 20000 applicants throughout India to work under the guidance of Prof. Kannan Moudgalya.
Developed a two layer spam filtering system using machine learning for the forums of Spoken Tutorials, a project by IIT Bombay and MHRD, Govt. of India.
Achieved an F1 score of 0.91 on the data and deployed the models using a Django based web application.
Technologies used: Sklearn, Keras, Django, AJAX, Bootstrap 4

Machine LearningData Analysis

Openebs project

Project Intern

Feb 2018 – May 2018 · 3 mos · India

Worked on the existing OpenEBS framework, and deployed a Go script using a Kube cluster.
Worked on weave scope, a JavaScript based framework used to visualize Kube clusters. Made multiple contributions to the WeaveScope repository.
Selected as the Top 5 interns in this program from amongst the 100 interns countrywide.
Technologies used: Docker, Kubernetes, Go, Git

KubernetesGo