Rushab M.

AI Researcher

New York City, New York, United States10 yrs 2 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in AI-driven investment solutions.
Specializes in NLP from alternative datasets.
Proven track record in quantitative research.

Stackforce AI infers this person is a quantitative researcher specializing in AI and NLP for finance.

Contact

rushab@seas.upenn.edu LinkedIn

Skills

Core Skills

Machine LearningNatural Language Processing

Other Skills

AlgorithmsApache SparkAssembly LanguageBayesian inferenceBayesian statisticsCC++Cascading Style Sheets (CSS)Data AnalysisDistributed SystemsFinancial AnalysisFinancial ModelingGitHTMLHadoop

About

Quantitative researcher specializing in the development and enhancement of alpha models for domestic and international equity. I build AI-driven solutions to support informed investment and sales decisions. My expertise includes integrating advanced NLP-based signals from alternative datasets and building customized AI agents for integrating internal and public data.

Experience

10 yrs 2 mos

Total Experience

2 yrs 1 mo

Average Tenure

4 yrs 1 mo

Current Experience

Lord, abbett & co. llc

Equity Quantitative Researcher

May 2022 – Present · 4 yrs 1 mo · New York City Metropolitan Area

Machine LearningPythonNatural Language ProcessingData Analysis

Goldman sachs

2 roles

Associate - Asset Management

Feb 2020 – May 2022 · 2 yrs 3 mos · New York, United States

Summer Analyst

May 2019 – Aug 2019 · 3 mos · Greater New York City Area

University of pennsylvania

Graduate Research Assistant

Sep 2018 – Feb 2020 · 1 yr 5 mos

Emotion impacts Speech recognition - Naacl SRW, 2019
Improving summarization by detecting (un)important clusters in text

Natural Language ProcessingData Analysis

Goldman sachs

Market Risk Strats (Summer Analyst)

May 2017 – Jul 2017 · 2 mos · Bangalore

• Was offered a full time position at Goldman Sachs - Risk, Bengaluru

Indian institute of technology, kanpur

Undergraduate Researcher

Jan 2017 – Nov 2017 · 10 mos · India

RNN BASED HIERARCHICAL CLASSIFICATION FOR WSD
Prof. Harish Karnick, IIT Kanpur
Developed an end-to-end hierarchical model in PyTorch for word
sense disambiguation based on WordNet sense keys
Used a shared LSTM encoder and a decoder at every node
Used a context-independent attention mechanism

New york office iitk

Intern

May 2016 – Jul 2016 · 2 mos

Built a model to extract useful information from raw html profiles to accommodate changes in webpage formats.
Information included names, skills, organizations, etc.

The university of texas at dallas

Research Intern

May 2016 – Jul 2016 · 2 mos

On Parameter Tying by Quantization, under Prof. Vibhav Goagate
Quantitatively analyzed the paper 'On Parameter Tying by Quantization' (AAAI 2016) when applied to logistic regression. The method is a regularization technique that sets constraints of similar parameters so as to prevent overfitting.

Bloodconnect foundation

2 roles

Vice President

Feb 2015 – Mar 2016 · 1 yr 1 mo

Vice President of Helpline, Kanpur
BloodConnnect works in the field of voluntary blood donation and towards eradicating blood shortage. BloodConnect is spread over more than 10 major cities across India.
In Helpline we work towards helping patients get blood on time. We also have a 24X7 Emergency helpline. The work involves contacting people and try to convince them to donate blood, coordinating with the patient's relatives and various blood banks for the timely fulfillment of every request.

Volunteer

Aug 2014 – Mar 2015 · 7 mos

Volunteered at Raktarpan - IIT Kanpur and BloodConnect as a member of National Social Service, IIT Kanpur.
Worked on emergency blood donation cases along with organizing donation camps and awareness sessions