Aranya Dan

Data Scientist

https://talent.gravityer.com/aranya-dan

Phd Student, ITV, RWTH Aachen

GermanyMember since June 26, 2026

Key Strengths

Demonstrated proficiency in scientific computing languages like Fortran, Matlab, and Python, particularly in numerical methods (WENO schemes).
Experience with C++ for performance-critical applications and system-level programming.
Exposure to various build systems (Makefile, CMake) and scripting (Shell).
Projects indicate an interest in image processing ('caltech-lane-detection', 'plots-to-tables') and numerical simulations, which are relevant to data science applications.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic in nature, focusing on numerical methods, scientific computing, and some image processing. This indicates a strong inclination towards research-oriented or highly technical roles. The diversity of technologies (Fortran, C++, Python, Matlab, Solidity) suggests adaptability, but the lack of team projects or collaborative descriptions makes it difficult to assess cultural fit for a typical corporate environment. The projects align with a data scientist role that involves heavy numerical computation or scientific modeling.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are minimal, and no psychometric or English test results are available.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

snake2virus

July 4, 2023 – July 4, 2023

snake2virus — GitHub repository

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capture-the-ether

August 28, 2022 – August 29, 2022

Solutions for capture-the-ether

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WENO5_3D_FORTRAN

March 19, 2018 – May 26, 2018

3D WENO 5th Order Code in Fortran

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WENO5_2D_NSsolver_FORTRAN

October 18, 2017 – May 29, 2018

2D viscous WENO 5th order implementation

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SWBLI_WENO5_2D_FORTRAN

October 15, 2017 – October 16, 2017

SWBLI_WENO5_2D_FORTRAN — GitHub repository

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WENO52D_fortran

October 11, 2017 – October 18, 2017

WENO52D_fortran — GitHub repository

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WENO51D_fortran

November 29, 2016 – May 28, 2018

WENO51D_fortran — GitHub repository

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plots-to-tables

February 25, 2016 – May 5, 2016

Given a set of scanned pdf pages as input, where each page has one or more plots embedded in text, converts them to a set of two-dimensional tables, one table per plot.

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caltech-lane-detection

July 25, 2015 – July 25, 2015

Automatically exported from code.google.com/p/caltech-lane-detection

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relaxed_astar

May 3, 2015 – February 18, 2015

relaxed_astar — GitHub repository

View Project

Key Strengths

Demonstrated proficiency in scientific computing languages like Fortran, Matlab, and Python, particularly in numerical methods (WENO schemes).
Experience with C++ for performance-critical applications and system-level programming.
Exposure to various build systems (Makefile, CMake) and scripting (Shell).
Projects indicate an interest in image processing ('caltech-lane-detection', 'plots-to-tables') and numerical simulations, which are relevant to data science applications.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are minimal, and no psychometric or English test results are available.

Aranya Dan

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit