Contact Us

Innovation

Bridging technology and innovation for smart solutions.

Expertise

Solutions

lazine@lazineholdings.com

1-414-544-5454

© 2024. All rights reserved.

Join Our Team at Lazine Holdings!

Lazine Holdings is growing, and we’re looking for talented students to join us on exciting projects in sports analytics, real estate AI, and data technology. We’re a technology-driven company, and we invite those who are ready to innovate and make an impact. Explore our current openings below to find the perfect fit for you!

Sports API Developer

Description: Lazine Holdings is seeking a Computer Science or Data Science student who is passionate about sports analytics to help build an advanced sports API. This API will go beyond existing lineup optimizers by incorporating real-time data and intricate algorithms.

Responsibilities: Design and develop a scalable sports API that integrates real-time data. Work on optimization algorithms to enhance lineup recommendations. Ensure high accuracy, data quality, and performance in the API.

Requirements: Experience with API development (Python, Flask, FastAPI, or similar). Proficiency with SQL databases and sports data libraries. Understanding of optimization algorithms and data processing techniques.

Real Estate AI Assistant Developer

Description: We’re developing a machine-learning-based AI assistant tailored for real estate professionals across the U.S., and we’re looking for a student with skills in AI and natural language processing. This assistant will provide insights, predict trends, and continuously learn from user interactions.

Responsibilities: Develop and train machine learning models specifically for real estate data. Implement natural language processing (NLP) capabilities for interactive responses. Refine the model to improve accuracy and user experience over time.

Requirements: Proficiency in machine learning frameworks (TensorFlow, PyTorch, etc.). Strong understanding of NLP and AI-driven chatbot functionality. Interest or experience in real estate technology is a plus.

Data Scrubbing and Retrieval Specialist

Description: We’re looking for a detail-oriented Data Engineering student to help us with data scrubbing and retrieval for sports and real estate projects. This role will involve data scraping, cleaning, and organizing to ensure that our data is accurate, structured, and ready for analysis.

Responsibilities:

Collect and clean data from multiple web sources. Remove duplicates, errors, and inconsistencies in the data.Organize and structure data for optimal access by other team members.

Requirements: Experience with web scraping tools (BeautifulSoup, Scrapy) and Python. Familiarity with data cleaning techniques and best practices. Knowledge of ETL (Extract, Transform, Load) processes.

Western Digital Storage Expert

Description:
Lazine Holdings is looking for a student skilled in data storage solutions, specifically Western Digital systems, to assist with setting up and managing our data storage. This role focuses on ensuring secure, scalable storage that aligns with our project needs.

Responsibilities: Set up and manage Western Digital storage solutions for optimal data storage. Ensure data security and accessible storage across the team. Optimize storage configurations to enhance performance and scalability.

Requirements: Familiarity with Western Digital storage or similar cloud storage systems. Understanding of large-scale data storage and data security practices. Background in IT or network storage management.

Real-Time Sports Data Specialist

Description: We’re seeking a student with a strong interest in sports and real-time data analytics to help us handle injury updates and live player data for our sports API. This role requires data streaming and scraping skills, with a focus on injury and player status updates.

Responsibilities: Develop and manage real-time data streams for sports data. Scrape and monitor sports news sources for up-to-date injury reports. Ensure accurate real-time data is fed into our sports API.

Requirements: Experience with real-time data platforms (e.g., Kafka, AWS Kinesis). Proficiency in data scraping and aggregation. Familiarity with sports data sources and injury reporting platforms.