DavidLEE

Data Scientist

https://talent.gravityer.com/davidlee

Stuttgart University. Wuhan University

Key Strengths

Demonstrated interest in Computer Vision and SLAM through multiple personal projects (SLAMbook, OpenCV_Annotated, slam_project, computer_vision).
Proficiency in C++ and CMake, essential for low-level performance-critical applications in data science and computer vision.
Exposure to machine learning concepts with projects like 'ML_in_Action' and 'scikit-learn_and_tensorflow', indicating foundational knowledge in the target role's domain.
Active engagement in competitive programming (leetcode) suggests problem-solving abilities.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects show a strong inclination towards self-learning and exploration in computer vision and machine learning, which aligns with a proactive and curious cultural fit. However, the lack of team-based projects or detailed experience makes it difficult to fully assess collaboration and broader cultural alignment. The target role 'Data Scientist' aligns with the candidate's project interests.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's experience is listed as 'Data Scientist' at 'Stuttgart University. Wuhan University' with a future start date, and no details on responsibilities or achievements are provided. No psychometric test results are available.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

OpenCV_Annotated

April 22, 2019 – December 27, 2020

studying OpenCV's Source Codes

View Project

slam_project

April 21, 2019 – May 31, 2019

little slam project

View Project

leetcode

July 22, 2018 – August 10, 2018

leetcode — GitHub repository

View Project

Cpp_Concurrency

April 23, 2018 – May 15, 2018

C++ concurrency

View Project

Documents

January 14, 2018 – October 21, 2018

Documents — GitHub repository

View Project

SLAMbook

January 1, 2018 – October 28, 2018

视觉SLAM 十四讲随书代码练习。Mac。

View Project

scikit-learn_and_tensorflow

November 13, 2017 – April 21, 2018

scikit-learn_and_tensorflow — GitHub repository

View Project

computer_vision

November 12, 2017 – November 25, 2018

computer_vision — GitHub repository

View Project

ML_in_Action

October 8, 2017 – January 14, 2018

machine learning in action

View Project

little_work

September 1, 2017 – October 24, 2017

little_work — GitHub repository

View Project

Key Strengths

Demonstrated interest in Computer Vision and SLAM through multiple personal projects (SLAMbook, OpenCV_Annotated, slam_project, computer_vision).
Proficiency in C++ and CMake, essential for low-level performance-critical applications in data science and computer vision.
Exposure to machine learning concepts with projects like 'ML_in_Action' and 'scikit-learn_and_tensorflow', indicating foundational knowledge in the target role's domain.
Active engagement in competitive programming (leetcode) suggests problem-solving abilities.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

DavidLEE

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit