Location
Zurich
Workload
Full-time
Responsibilities
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.
Profile
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.
* Mathematik
* Retail
* Python
* AWS
* R
* SQL
* Bachelor
* Master
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