Rohan Keshari

Data Scientist

Bengaluru, Karnataka, India9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Developed strategic trading models enhancing financial decision-making.
Created fraud detection dashboards for real-time insights.
Passionate about technology and shaping the digital future.

Stackforce AI infers this person is a Fintech Data Scientist with strong quantitative analysis and algorithm development skills.

Contact

rohan.keshari@aviso.com LinkedIn

Skills

Core Skills

Quantitative AnalysisAlgorithm DevelopmentData AnalysisFraud Detection

Other Skills

Algorithmic Trading SignalsAlgorithmsAmazon Web Services (AWS)Analytical SkillsArtificial Intelligence (AI)Autodesk TinkercadBack-End Web DevelopmentCC++Cascading Style Sheets (CSS)ChatbotsCode ReviewCommunicationCompetitive ProgrammingComputer Science

About

Graduated from IIT Ropar. I am passionate about technology, data, & coding. Looking forward to shape the future of digital world! Please contact me at kesharirohan008@gmail.com for full time opportunities.

Experience

9 mos

Total Experience

9 mos

Average Tenure

Current Experience

Hsbc

Data Scientist

Jul 2024 – Apr 2025 · 9 mos · Kolkata · On-site

Futures first

Quant Developer

May 2023 – Jul 2023 · 2 mos · Gurgaon

Worked extensively on analyzing economic data and Eurodollar outright market data to develop and implement strategic trading models, enhancing financial analysis and decision-making processes for Market.
Researched, and implemented the various Interest rate models while generating forward curves, conducting rigorous backtesting, and developing algorithmic trading signals.
Investigated strategies for optimizing trading signals and conducted comparative analyses to evaluate their respective variances and merits

Economic Data AnalysisStrategic Trading ModelsInterest Rate ModelsAlgorithmic Trading SignalsQuantitative AnalysisAlgorithm Development

Simpl

Data Science and Fraud Analyst

Jun 2022 – Jul 2022 · 1 mo · Bengaluru, Karnataka, India

Worked on building insightful dashboards on Qliksense for the Anti Fraud department by analysing current/emerging fraud patterns, demographics and identifying appropriate business metrics and Key Risk Indicators.
Prepared an automated emailer for daily review of fraud reports depicting Total Payment Volume (TPV), percentage TPV and net losses with filter blocks corresponding to the particular day

QliksenseFraud AnalysisDashboard DevelopmentEmail AutomationData AnalysisFraud Detection