Nabeel Amjad

is looking for freelance projects. 🔎

Praktikum, Breeding Information Scientist, KWS SAAT SE & Co. KGaA

Göttingen, Deutschland

Fähigkeiten und Kenntnisse

Python
SQL
Bash (Unix shell)
Data Visualization
Tableau Software
Windows
Linux
Data Analysis
Python pandas
Python numpy
Microsoft Office Excel
Git
Atlassian Bitbucket
Selenium WebDriver
Web Services
Support
Software Development
Tableau
Google Analytics
Communication skills
Team work
Commitment
Reliability
Microsoft Power BI
Power Automate

Werdegang

Berufserfahrung von Nabeel Amjad

  • Bis heute 1 Jahr und 5 Monate, seit Jan. 2023

    Breeding Information Scientist

    KWS SAAT SE & Co. KGaA

    Utilized Microsoft Power Platform to develop a product for the breeders. Practised Agile methodology as part of a team to develop software solutions for plant breeding information management. Built a strong network of relationships with colleagues and users to support future software development initiatives. Maintained flexibility and willingness to take on additional responsibilities as needed.

  • 10 Monate, Juni 2020 - März 2021

    Quantitative Developer

    Citibank

    Worked as Quantitative Developer Intern at Citibank in Institutional Client Group. Responsibilities Included: • Developing and refactoring Pricing libraries for market quantitative analysis testing framework. • Develop a monitoring tool for team-specific bitbucket changes. • Perform data analysis and data visualization on the dataset. • Configuring Python modules on the TeamCity cloud platform.

Ausbildung von Nabeel Amjad

  • Bis heute 2 Jahre und 2 Monate, seit Apr. 2022

    Applied Data Science

    Georg-August Universität Göttingen

    Major Courses: Application Development, Artificial Intelligence, Databases, Computer Networks, Practical Software engineering, Tools of Software Projects, Programming Languages, Basic legal and Business Knowledge, and Principles of economics.

  • 3 Jahre und 10 Monate, Sep. 2017 - Juni 2021

    Computer Science

    Eötvös Loránd University

    Thesis: The purpose of the thesis is to propose a student performance model based on data gathered through the e-learning management system. Machine learning techniques such as random forest regression and multivariate regression are used to evaluate students’ performance. Based on the top three features of the dataset that contributes most to the performance I develop an interactive dashboard to get insights into data deployed on the cloud platform.

Sprachen

  • Englisch

    Fließend

  • Deutsch

    Grundlagen

Interessen

Cricket
Photography
Travel

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