The Senior Data Scientist plays a critical role within the Data Science team, driving advanced analytics, machine learning, and predictive modeling initiatives. This role focuses on developing strategic models and solutions to optimize business operations, enhance customer experience, and maximize revenue. The Senior Data Scientist must possess deep technical expertise as they will play a critical role in shaping the data science strategy. The Senior Data Scientist will collaborate closely with cross-functional teams, providing leadership in analytical projects while remaining hands-on with coding and model development.
Who We Are
At CubeSmart, we’re intentional about culture. You can experience it everywhere from our mission statement of “genuine care” to our “It’s What’s Inside That Counts” tagline to calling each other “teammates” rather than employees. This spirit fosters a fun and collaborative environment that has resulted in our rapid growth and being recognized amongst the top in our industry.
CubeSmart’s award-winning team is made up of people who genuinely care. Teammates care about our customers and the life events and/or business needs they are facing. Teammates are passionate, responsible, and understanding. The CubeSmart team is made up of people who have a can-do attitude, are committed to their own success and the success of the company, and lead by example. If this sounds like a team and culture that matches your personal values and motivations, we want to hear from you.
Responsibilities
- Advanced Analytics and Modeling
- Develop and implement advanced analytics and machine learning models to solve complex business problems.
- Oversee the design and execution of predictive models for customer segmentation, pricing strategies, and inventory management.
- Provide expert guidance on the theoretical foundations of statistical models and machine learning techniques, ensuring the selection of appropriate methods is grounded in a deep understanding of the problem context, underlying assumptions, and potential trade-offs.
- Ensure the accuracy, quality, and scalability of data science solutions.
- Assist in the creation and evolution of state-of-the-art MLOps implementations.
Strategic Collaboration
- Work with cross-functional teams, including marketing, operations, investments, and finance, to identify data-driven opportunities.
- Provide actionable insights and recommendations to senior leadership based on analytical findings.
- Lead projects aimed at optimizing business operations, improving customer experience, and increasing revenue.
Experimentation and Testing
- Design and implement testing and experimentation strategies, including A/B testing and controlled experiments.
- Analyze results from experiments to measure the effectiveness of business strategies.
- Develop guidelines and best practices for consistent and reliable experimentation results and monitoring.
Data Infrastructure and Governance
- Collaborate with IT and data engineering teams to ensure data infrastructure is reliable and scalable.
- Establish and maintain data governance practices to ensure data quality, consistency, and security.
- Advocate for best practices in data management.
Leadership and Mentorship
- Mentor junior data scientists, providing guidance on best practices and technical problem-solving.
- Foster a collaborative and innovative team culture, promoting continuous learning and professional development.
Communication and Stakeholder Management
- Communicate complex analytical concepts and insights to non-technical stakeholders, including executives.
- Develop and deliver presentations, reports, and dashboards to convey data-driven.
- Build and maintain strong relationships with internal stakeholders to understand their needs and provide tailored data science solutions.
Qualifications
- Master’s degree or Ph.D. in Economics, Data Science, Statistics, Mathematics, or a related field.
- Minimum of 5 years of experience in data science, analytics, or a related field.
- Proven track record in developing and deploying machine learning models and advanced analytics solutions.
- Proficiency in programming languages such as Python and SQL, and big data technologies like Databricks.
- Strong problem-solving skills and strategic thinking ability.
- Excellent communication skills for explaining technical concepts to non-technical audiences.
- Strong interpersonal skills for building relationships with stakeholders.
