<p>Overview</p> <p>The Machine Learning Data Engineer plays a crucial role in supporting the data science team by managing the entire data lifecycle with a focus on machine learning support, starting from acquiring data from various sources to preparing and serving it for machine learning pipelines. This includes ensuring data integrity, managing large-scale data processing, implementing feature engineering, and maintaining data workflows that support continuous integration and deployment of machine learning models. Reporting directly to the Senior Manager of Data Science, this role requires a deep technical background, with particular emphasis on Databricks, a strong understanding of data infrastructure, and a passion for building scalable and efficient machine learning systems. The ideal candidate will have experience in Databricks with data preprocessing, feature engineering, MLOps, model deployment, and maintaining model performance in a production environment.</p> <p>CubeSmart is a publicly traded real estate investment trust (REIT) focused on the development, acquisition, disposition, and management of self-storage facilities. CubeSmart is headquartered in Malvern, PA, a suburb of Philadelphia, and is one of the largest self-storage owners and operators in the United States, with more than 1500 locations nationwide.</p> <p>Over the past five years, CubeSmart has grown significantly, acquiring approximately $1.5 billion in assets. Our growth is possible because of our 3,000 teammates across the country who work together to grow the company, serve our Customers, and deliver results through a culture of open communication and collaboration. We are excited to have you join our team and grow with us!</p> <p>Responsibilities</p> <p>Data Gathering and Organization:</p> <ul> <li>Collect, clean, and organize large datasets from various internal and external sources. </li><li>Ensure data quality and integrity by implementing robust data validation and cleaning processes. </li><li>Partner with the Data Engineering team to build, maintain and migrate data pipelines that support data science initiatives. </li></ul> <p>Feature Engineering:</p> <ul> <li>Develop, refactor, and implement feature engineering pipelines to transform raw data into meaningful features for machine learning models. </li><li>Collaborate with data scientists to understand the requirements for feature selection and transformation. </li><li>Continuously explore and implement new techniques to improve feature relevance and model performance. </li></ul> <p>Model Deployment and Monitoring:</p> <ul> <li>Partner with the Data Engineering team to deploy data science models into production environments using best practices for scalability and reliability. </li><li>Implement monitoring systems to track model performance and detect issues such as data drift or performance degradation. </li></ul> <p>Collaboration and Communication:</p> <ul> <li>Work closely with data scientists, analysts, and stakeholders to understand business needs and translate them into technical requirements. </li><li>Document processes, models, and workflows to ensure transparency and reproducibility. </li><li>Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner. </li></ul> <p>Continuous Improvement:</p> <ul> <li>Stay updated with the latest advancements in machine learning, data engineering, and related technologies. </li><li>Participate in code reviews, knowledge sharing sessions, and continuous learning activities to foster a culture of innovation and excellence. </li><li>Identify and implement opportunities for improving the efficiency and effectiveness of machine learning workflows. </li></ul> <p>Qualifications</p> <ul> <li>Education: Bachelor's degree in Marketing, Analytics, Business Administration, or a related field; advanced degree preferred. </li><li>Experience: 5+ years in analytics, with at least 3 years in marketing analytics and 2+ years in team management. </li><li>Proficiency in marketing analytics tools (e.g., Google Analytics, Adobe Analytics). </li><li>Experience with data visualization platforms (e.g., Tableau, QlikSense). </li><li>Collaboration with data science teams on predictive modeling. </li><li>Familiarity with SQL and Python for data analysis. </li><li>Understanding of digital marketing channels and strategies. </li><li>Ability to translate data insights into actionable business strategies. </li><li>Excellent communication skills, strong project management, and a strategic mindset focused on customer engagement. </li></ul> <p>We are an Equal Opportunity Employer, Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity</p> <p>#LI-MT1</p>