Data Operations Analyst

MaxHome.AI is a pioneering startup dedicated to revolutionizing the real estate industry in the United States. With the real estate sector valued at $2 trillion and realtor commissions exceeding $100 billion, MaxHome.ai aims to leverage artificial intelligence and machine learning to empower real estate agents, optimize their workflows, and enhance their revenue potential. We are a dynamic team of seasoned builders with deep experience in real estate tech, passionate about driving positive change in the industry. We are seeking a highly motivated and talented founding data scientist to join our team and help shape the future of our company.

JOB DESCRIPTION:

As a Data Labelling Analyst at MaxHome.AI, you will play a pivotal role in fuelling the development of our AI-native SaaS platform. You will be responsible for meticulously annotating and labelling real estate data to train machine learning models that automate various aspects of real estate agent workflows. This role offers an exciting opportunity to be part of a fast-paced startup environment and contribute to shaping the future of our company.

RESPONSIBILITIES:

• Data Annotation and Labeling: Accurately annotate and label real estate data, including property images, listings, and textual descriptions, to create high-quality training datasets for machine learning algorithms.
• Quality Assurance: Conduct comprehensive quality checks on annotated data to ensure precision, consistency, and relevance to project objectives. Identify and rectify any labeling errors or inconsistencies.
• Dataset Management: Organize and maintain labeled datasets in a structured manner, adhering to version control best practices. Collaborate with data engineers and scientists to ensure seamless integration of annotated data into machine learning pipelines.
• Domain Expertise: Develop a deep understanding of the real estate domain, including property types, market trends, and industry-specific terminology. Apply domain knowledge to optimize data labeling processes and enhance model performance.
• Workflow Optimization: Continuously evaluate and enhance data labeling workflows to improve efficiency and scalability. Propose and implement tools, techniques, and automation solutions to streamline labeling tasks.
• Collaboration: Collaborate closely with cross-functional teams, including data scientists, engineers, and product managers, to understand project requirements and ensure alignment on labeling criteria and objectives.
• Documentation: Document labeling guidelines, standards, and best practices to ensure consistency and facilitate knowledge sharing within the team. Maintain documentation up-to-date with any changes or enhancements to the labeling process.

REQUIREMENTS:

• Bachelor's degree in any field.
• Minimum of 2 years of experience in data labeling, preferably in the real estate or related domain.
• Proficiency in data annotation tools and platforms, such as Labelbox, Amazon SageMaker Ground Truth, or similar.
• Strong attention to detail and ability to maintain accuracy in labeling tasks, particularly in interpreting real estate data attributes.
• Excellent communication skills and ability to collaborate effectively in a fast-paced startup environment.
• Familiarity with machine learning concepts and workflows, with a desire to expand knowledge in this area.
• Proven ability to work independently and as part of a team, with a proactive and results-driven mindset.
• Experience with version control systems (e.g., Git) and scripting languages (e.g., Python) is a plus.
• Passion for real estate technology and a keen interest in shaping the future of the industry through AI and machine learning.