Support the Data Scientist in developing data-driven strategies and products by extracting, manipula
岗位职责
As a Data Scientist Intern, you will support the Data Scientist within the Product Management team. Your role focuses on developing strategies and products centered on extracting, manipulating, and mathematically modeling process data. You will identify use cases and implement them within the company's portfolio.
Key responsibilities include:
- Assisting in the creation and application of statistical and/or Machine Learning models for data analysis and product development.
- Supporting the extraction, cleaning, and preprocessing of data from various sources to ensure quality and usability.
- Collaborating with the team to identify and define data-driven use cases that align with product goals.
- Implementing models and solutions into the existing product portfolio, ensuring integration and performance.
- Conducting exploratory data analysis to uncover insights and trends that inform product strategy.
- Documenting methodologies, results, and processes to maintain clear records and facilitate knowledge sharing.
- Participating in team meetings and contributing to discussions on data strategy and product improvements.
申请条件
- Currently pursuing or recently completed a degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
- Basic understanding of statistical modeling and Machine Learning concepts.
- Proficiency in programming languages such as Python or R.
- Familiarity with data manipulation tools and libraries (e.g., pandas, NumPy).
- Strong analytical and problem-solving skills.
- Ability to work collaboratively in a team environment.
- Excellent communication skills in Italian and English.
- Prior internship or project experience in data analysis is a plus.
雇主简介
Körber Technologies is a technology company that develops products and strategies for process data extraction, manipulation, and mathematical modeling, with a focus on implementing machine learning and statistical models.