Data Science Intern
Gaming Innovation Group, Malta
Job Description
At GiG, we pride ourselves on housing a world-class team of data scientists, data analysts, and machine learning engineers. We are at the forefront of revolutionizing the digital landscape, leveraging data-driven insights to propel our company and partners towards unparalleled success.
Our team is dedicated to harnessing the power of data to drive informed decision-making, develop groundbreaking algorithms, and craft intelligent solutions that shape the future of our industry. From predictive analytics to machine learning models, we thrive on transforming complex data into actionable strategies that drive tangible results.
As an intern at GiG, you will have the unparalleled opportunity to immerse yourself in a dynamic environment alongside industry pioneers. You'll gain hands-on experience tackling real-world challenges, collaborating with experts, and honing your skills in a supportive, innovative atmosphere.
Project:
At GiG, we're constantly innovating to provide unparalleled experiences for online casino operators and their users. Our Game Recommendation Engine (GRE) harnesses the power of AI-driven technology to revolutionize game configuration, akin to the personalised experiences offered by leading media streaming platforms.
Working seamlessly with Frontend interfaces, Content Management Systems, and CRM solutions, GiG's GRE streamlines content selection, eliminating manual processes through advanced algorithms and filtering systems. By leveraging game, user, and market data, it generates tailored game lists, predicting optimal rankings and preferences for individual users or user groups. The GRE is a self-learning autonomous solution that continuously refines its recommendations through real-time feedback, adapting to evolving player profiles and behaviors.
What you'll be doing
- Scraping Mechanism Enhancement: Upgrade the GRE's scraping mechanism with modern frameworks for better data collection.
- Data Integration: Integrate public data with internal databases using fuzzy-logic and machine learning algorithms.
- Recommendation Algorithm Development: Contribute to designing and implementing a new recommendation algorithm based on game metadata similarities.
What's in it for you?
- Research and Learning: Explore modern scraping frameworks and algorithms relevant to the project.
- Development and Implementation: Code, test, and deploy updates to improve the GRE's scraping mechanism.
- Data Analysis and Integration: Analyze data, identify patterns, and assist in integrating datasets effectively.
- Algorithm Design and Testing: Prototype, test, and refine recommendation algorithms, ensuring performance and relevance.
- Documentation and Reporting: Maintain clear documentation, contribute to project reports, and communicate progress effectively.
Requirements
The skills required for the intern to successfully contribute to the project include:
- Programming Proficiency: Strong programming skills in languages such as Python, and familiarity with libraries/frameworks for web scraping, data manipulation (e.g., BeautifulSoup, Scrapy, pandas), and machine learning (e.g., scikit-learn, TensorFlow, PyTorch).
- Data Analysis and Interpretation: Ability to analyze and interpret large datasets, identify patterns, and extract meaningful insights using statistical methods and data visualization tools (e.g., matplotlib, seaborn).
- Algorithm Design and Implementation: Understanding of machine learning algorithms and their application in recommendation systems. Proficiency in designing, implementing, and optimizing algorithms for data processing and analysis.
- Data Integration: Knowledge of data integration techniques and experience working with different types of data sources (e.g., APIs, databases). Familiarity with techniques for matching and merging datasets using fuzzy logic or machine learning approaches.
- Critical Thinking and Problem-Solving: Strong analytical and problem-solving skills to tackle complex challenges and propose innovative solutions. Ability to approach problems systematically, experiment with different approaches, and adapt strategies based on results.
- Collaboration and Communication: Effective communication skills to collaborate with team members, present findings, and discuss technical concepts. Ability to work collaboratively in a fast-paced environment, share knowledge, and contribute to team goals.
- Documentation and Reporting: Attention to detail and ability to maintain clear and organized documentation of code, algorithms, and project progress. Capability to prepare comprehensive reports and presentations to communicate findings and outcomes effectively.