Sr. Manager, Data Science

The Senior Manager of Data Science will play a pivotal role in driving data-driven decision-making and strategic insights for CubeSmart. This leader will oversee a team of data scientists, utilizing advanced analytics, machine learning, and predictive modeling to optimize business operations, enhance customer experience, and maximize revenue. The ideal candidate is a strategic thinker with a deep technical background, exceptional leadership skills, and a passion for leveraging data to solve complex business problems. While the primary responsibility is managing the team, the ideal candidate must also be hands-on with coding and technical problem-solving, demonstrating their technical expertise to support and advance the team's projects and initiatives.

• Lead, mentor, and develop a high-performing team of data scientists.
• Foster a collaborative and innovative team culture, promoting continuous learning and professional development.
• Set clear goals and performance expectations for the data science team, ensuring alignment with company objectives.
• Allocate resources effectively, managing project priorities and timelines.
• Promote a data-driven, scientific culture throughout the company by advocating for data-driven approaches and evidence-based decision-making.

• Develop and execute a strategic vision for the data science function that aligns with CubeSmart's broader business goals.
• Identify and prioritize high-impact data science projects and initiatives that drive business growth and efficiency.
• Establish and manage a data science roadmap, guiding the team's focus on projects with the highest strategic value.

• Develop and implement advanced analytics and machine learning models to address key business challenges and opportunities, particularly focused on maximizing revenue.
• Oversee the design and execution of predictive models to enhance customer segmentation, pricing strategies, and inventory management.
• Ensure the accuracy, quality, and scalability of data science solutions.

• Design and implement testing and experimentation strategies, including A/B testing and controlled experiments.
• Analyze the results of experiments to measure the effectiveness of business strategies and initiatives.
• Develop guidelines and best practices for testing and experimentation to ensure consistent and reliable results.

• Collaborate with cross-functional teams, including revenue management, marketing, operations, investments, and finance, to identify data-driven opportunities and support strategic initiatives.
• Provide actionable insights and recommendations to senior leadership based on data analysis and modeling results.
• Lead projects aimed at optimizing business operations, improving customer experience, and increasing revenue.

• Communicate complex analytical concepts and insights to non-technical stakeholders, including executives and department heads.
• Develop and deliver presentations, reports, and dashboards that effectively convey data-driven insights and recommendations.
• Build and maintain strong relationships with internal stakeholders to understand their needs and provide tailored data science solutions.
• Act as a liaison between the data science team and other departments, ensuring data science initiatives are aligned with broader business goals.

• Establish and maintain best practices for data science methodologies, tools, and frameworks.
• Implement processes for continuous improvement in data science workflows and project management.
• Ensure compliance with data governance and security standards.

• Master's degree or Ph.D. in Economics, Data Science, Statistics, Mathematics, or a related field.
• 8 or more years of experience in data science, analytics, or a related field
• Proven track record in leading data science teams, particularly focused on pricing strategy, marketing optimization, investment analysis or related fields.
• Strong background in developing and deploying machine learning models and advanced analytics solutions.
• Proficiency in programming languages such as Python and SQL and big data technologies, such as Databricks.
• Strong problem-solving skills and the ability to think strategically about data and business.
• Experience in applying advanced analytical techniques to business problems.
• Ability to translate complex data insights into actionable business recommendations.
• Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
• Strong interpersonal skills and the ability to build relationships with stakeholders at all levels of the organization.

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