Divyansh J.

AI Researcher

San Francisco, California, United States9 yrs 9 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in Generative AI and Machine Learning.
Proven track record in cybersecurity innovations.
Strong background in predictive analytics and operational optimization.

Stackforce AI infers this person is a Data Science and AI specialist in the tech industry.

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Skills

Core Skills

Artificial Intelligence (ai)Machine LearningCybersecurityAi-driven Intelligent SolutionsData ScienceDemand ForecastingDeep LearningMarket Segmentation

Other Skills

Python (Programming Language)Cloud ComputingGraph Neural NetworksPredictive AnalyticsModel interpretabilityUnsupervised AI modelsUnsupervised machine learningSensitivity analysisTensorFlowMarket Segmentation analyticsCollaborative FilteringETL workflowMachine learning modulesClassification operatorClustering operator

About

AI innovator with diverse experience across domains, driving cutting-edge research and shaping transformative business solutions. From advanced Machine Learning to Generative AI, I turn complex data into impactful insights, optimizing processes and decision-making. My work spans predictive analytics, cybersecurity, and operational innovation, delivering tangible results and solving critical challenges.

Experience

Nvidia

5 roles

Staff Data Scientist

Promoted

Jul 2023 – Present · 2 yrs 8 mos · Santa Clara, California, United States

NVIDIA’s Applied Data Science group, RAPIDS.
● Leading the development of innovative unstructured and structured Generative AI solutions, contributing to NVIDIA’s cutting-edge AI advancements.

Artificial Intelligence (AI)Machine LearningData SciencePython (Programming Language)Cloud Computing

Senior Data Scientist

Feb 2021 – Jul 2023 · 2 yrs 5 mos · Santa Clara, California, United States

● Pioneered asset network mapping and cyber-threat detection systems using Graph Neural Networks (GNNs) for both internal IT and external clients.
● Implemented cyber digital fingerprinting solutions with NVIDIA Morpheus to enhance cybersecurity.
● AI-driven predictive management for NVIDIA’s data centers, optimizing operations through advanced machine learning models.

Graph Neural NetworksCybersecurityPredictive AnalyticsMachine Learning

Data Scientist III

Promoted

Apr 2019 – Jul 2021 · 2 yrs 3 mos · Santa Clara, California, United States

● Project Lead for deploying comprehensive AI-driven intelligent solutions to streamline operational processes.
● Developed and optimized AI models for test process automation, defect detection, yield prediction, and anomaly detection in production pipelines.
● Led cross-functional teams in ensuring model interpretability for machine learning applications across various business verticals.

AI-driven intelligent solutionsMachine LearningModel interpretability

Data Scientist II

Jul 2017 – Apr 2019 · 1 yr 9 mos · Santa Clara, California, United States

● Developed demand forecasting models for NVIDIA’s Consumer & Enterprise products, enhancing strategic decision-making.
● Created unsupervised AI models to derive insights from GeForce Gaming, driving key business decisions.

Demand forecastingUnsupervised AI modelsData Science

Data Science Intern

Jan 2017 – May 2017 · 4 mos · Santa Clara, California, United States

● Implemented unsupervised machine learning models to forecast the growth potential of new game releases.
● Developed a sensitivity analysis model to predict GPU demand in response to new game title releases.

Unsupervised machine learningSensitivity analysis

Usc gamepipe laboratory

Deep Learning Researcher

Aug 2016 – Dec 2016 · 4 mos · Greater Los Angeles Area

● Currently using TensorFlow's Deep Machine Learning library to design video game levels for Tower defense gaming applications
● Research Supervisor - Prof. Scott Easley (Associate Director, USC Gamepipe Labs)

Deep LearningTensorFlow

Amazon

Software Developer Intern

May 2016 – Aug 2016 · 3 mos · Greater Seattle Area

● Amazon Instant Video Playback Team

Ideata analytics

2 roles

Data Scientist

Jan 2015 – Jun 2015 · 5 mos · India

● Expedited the incumbent Market Segmentation analytics by 30% over the previous model by optimizing the statistical model.
● Devised and programmed an Explicit Collaborative Filtering Recommendation operator that yielded 'personalized recommendations'.
● Successfully Programmed and tested data ingestion from Cassandra, HDFS and Hive to an ETL workflow
● Implemented feature scaling using Principal Component Analysis.
● Application Deployment on Google Compute Engine.
● Technologies Used : Apache Spark (Mllib), Scala and Python.

Market Segmentation analyticsCollaborative FilteringETL workflowData ScienceMarket Segmentation

Machine Learning Summer Intern

Apr 2014 – Jun 2014 · 2 mos · India

Developed machine learning modules that encompasses
● fuzzy matching and lexical clustering operator.
● Multi-class Classification operator (naive Bayes, SVM).
● K-means Clustering operator.

Machine learning modulesClassification operatorClustering operator

Webskyinfotech

Android Application Developer (Summer Intern)

Apr 2013 – Jun 2013 · 2 mos · India

● Developed an android application that suggested employees an optimal path to clients' address while tracking their progress to facilitate efficient service to clients.
● Developed a chat application that aided communication between managers and employees.

Android Development