Minnie Kabra

AI Researcher

Grenoble, Auvergne-Rhône-Alpes, France10 yrs 6 mos experience

AI EnabledHighly Stable

Key Highlights

Over 6 years of experience in analytics and AI.
Expert in building machine learning models for fraud detection.
Strong background in NLP and GenAI technologies.

Stackforce AI infers this person is a Fintech and Cybersecurity expert with strong analytics and AI capabilities.

Contact

minniekabra@gmail.com LinkedIn

Skills

Core Skills

Artificial Intelligence (ai)Machine LearningAnalyticsData Science

Other Skills

AlgorithmsBusiness AnalyticsBusiness DevelopmentCC++ LanguageCollaborative Problem SolvingData MiningDeep LearningEnglishFinancial AnalysisFraud PredictionFraud Risk AnalysisGenAIHTMLJavaScript

About

Working in analytics for ~6.5 years has developed an ability to ask 'Why are we doing this work, and what would be it's impact?'. And though I worked in credit & fraud risk, I think that analytics can be applied to any spectrum of the job. I like AI. Particularly, I adore learning about the algorithms. and their expertises. Regularly use GenAI, and technology related to it. Plus, my experience in analytics have added an extra dimension to to learning about AI algos 'Where the idea of this algorithm originate from, and where can it be applied?'

Experience

Getalp

PHD Student

Mar 2025 – Present · 1 yr · Grenoble, Auvergne-Rhône-Alpes, France · On-site

American express

4 roles

Senior AI Researcher/Senior Manager

Jun 2022 – Feb 2025 · 2 yrs 8 mos

Working in the field of NLP. Use GenAI regularly in the work. Have also worked on classical ML algorithms

NLPGenAIMachine LearningArtificial Intelligence (AI)

Analytics Manager

Promoted

May 2020 – May 2022 · 2 yrs

Lead a team of analysts to secure entire digital journey of customer from third party fraud. Build machine learning (including deep learning) based models to predict fraud risk.

Machine LearningDeep LearningFraud PredictionAnalytics

Assistant Manager

Promoted

Aug 2018 – May 2020 · 1 yr 9 mos

Build multiple ML based models to predict different kinds of fraud risk, in particular - First party fraud & Third party fraud.

Machine LearningFraud Risk AnalysisAnalytics

Business Analyst

Jan 2016 – Aug 2018 · 2 yrs 7 mos

Did extensive analytics on fraud risk. Build ML based model to predict fraud risk at the point of sale.

AnalyticsMachine Learning

J k lakshmipat university

Guest Professor

Mar 2021 – Jul 2021 · 4 mos · India

Taught Multivariate Calculus in JKLU master's program - LSEF-UMASS (Exchange program with University of Massachusetts Amherst)

Fireeye, inc.

2 roles

Software Development Engineer

Jul 2015 – Dec 2015 · 5 mos · Greater Bengaluru Area

Data Scientist

May 2014 – Jul 2014 · 2 mos · Bengaluru, Karnataka, India

I have developed a software which uses Machine Learning techniques to predict maliciousness of a process running on a system.
I used random forest classifier as the classifier. Once trained, Random Forest classifier is used to predict maliciousness. Root to leaf-node path of decision tree inside random forest classifier can be thought of as learnt “inferred-rule”.
To improvise the accuracy of the classifier, I used cross validation, feature importance, Jaccard Similarity and correlation among the data.
Also, d3 visualization(Stacked Bar Chart) was implemented to detect hidden patterns among sub classes in training and test data
I have researched how bayesian formula can be used for botnet detection(based on DNS similarity) and A/B testing