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Assessing your cultural and operational fit
JPMorgan
Data Scientist
June 16, 2026 – Present
GHArchive-data-analysis
July 20, 2020 – July 21, 2020
Analyzing GHArchive KPIs using Pyspark
View ProjectPredicting-number-of-failures
January 21, 2020 – January 23, 2020
To predict the times a system will fail in the next hour when given timestamp of failures
View ProjectCustomer-Quality-Prediction
January 21, 2020 – January 23, 2020
To determine which set of customers the marketing firm should contact to maximize profit.
View ProjectFradulent-Detection
October 23, 2019 – October 23, 2019
Fradulent-Detection — GitHub repository
View ProjectTrie-Auto-complete-score
September 26, 2019 – September 26, 2019
Trie-Auto-complete-score — GitHub repository
View ProjectOnline-News-Popularity-using-ML-algorithms
August 26, 2019 – August 26, 2019
Classification Problem - UCI Dataset
View ProjectHousing-Price-Prediction-using-ML-algorithms
August 26, 2019 – August 26, 2019
Regression Problem - Kaggle Dataset
View ProjectPioneering-Effect-of-Industrial-Goods-Industries
August 25, 2019 – August 26, 2019
The focus of this research is to answer the following question: Does order of entry in an industrial goods industry have a major role to play in sustaining competitive advantages?
View ProjectCultural Fit Analysis
The candidate's projects are exclusively personal, which limits insight into collaborative work environments or contributions to team-based initiatives. While the projects align with a Data Scientist role, the lack of diverse project types (e.g., open-source contributions, team projects) or detailed descriptions makes it difficult to fully assess cultural fit beyond individual technical interest.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, but a current role at JPMorgan as a Data Scientist is mentioned, which creates a discrepancy. Project descriptions are brief, limiting insight into communication style or collaboration.