Spacewise is an innovative B2B SaaS proptech company headquartered in Zurich, Switzerland, with a rapidly expanding presence. Spacewise is revolutionizing the way commercial real estate landlords market, manage, and monetize their portfolios and spaces online to supercharge the value of their consumer facing properties. Spacewise also operates the premier online marketplace for short-term, pop-up, and promotional spaces.

For landlords, we provide user-friendly software tools to digitize property and space inventory for seamless space marketing and management. Our platform is trusted by major organizations such as Regency Centers and Centennial in North America; and Migros, Coop, SBB, Swiss Post, and Wincasa in Europe, just to name a few. Furthermore, we enable lead generation and booking activities for many of the world’s most renowned brands. Tenants of all sizes use our platform to effortlessly search, evaluate, and book the perfect location for their marketing activations, events, pop-ups, and promotions.

Are you passionate about digital transformation and helping to shape the future of one of the biggest asset classes in the world? Do you like working in an innovative, fast-paced environment? If so, the role as Data Scientist at Spacewise could be the perfect opportunity for you.

• Develop predictive models and algorithms that analyze various data inputs, including location intelligence, foot traffic, and economic trends, to improve decision-making processes.
• Collaborate with cross-functional teams (engineering, product, and business) to integrate machine learning models and data insights into the product ecosystem.
• Identify, collect, and analyze relevant data sources to deliver insights that enhance property pricing strategies, space utilization, and tenant matching.
• Create and refine forecasting models to predict future trends and outcomes, such as foot traffic patterns, sales potential, and space demand.
• Perform exploratory data analysis and statistical modeling to understand key business drivers and deliver actionable recommendations.
• Build and maintain scalable data pipelines to enable real-time analytics and reporting.
• Communicate complex analytical results to both technical and non-technical stakeholders, contributing to the strategic direction of the company.

• Degree in Data Science, Statistics, Applied Mathematics, Computer Science, or related field.
• Proven experience in building machine learning models and algorithms, preferably within the real estate, retail, or spatial analytics domains.Strong proficiency in data analysis and visualization tools (e.g., Python, R, SQL, Pandas, Matplotlib).
• Experience working with large datasets and applying statistical techniques such as regression, clustering, and time-series analysis.Familiarity with location-based analytics and spatial data, including the use of geospatial data for forecasting and analysis.
• Experience developing pricing algorithms or revenue management systems is a strong plus.Ability to communicate complex concepts clearly to both technical and business teams.
• Familiarity with cloud-based platforms such as AWS, GCP, or Azure for data storage and analysis.
• Strong problem-solving skills and the ability to work independently or as part of a team.

Preferred Qualifications:

• Experience with recommendation systems or personalization algorithms.
• Knowledge of optimization techniques for pricing and inventory management.
• Familiarity with foot traffic data, sales potential forecasting, and revenue optimization strategies in commercial spaces.

• Competitive salary and benefits package.
• Opportunity to work in a dynamic and innovative environment at the intersection of real estate and technology.
• Remote-friendly workplace with flexible working hours.
• Growth opportunities in a rapidly scaling company.

Please submit your resume and a cover letter detailing your experience and why you're a good fit for this role.