Spacewise

Data Scientist

Spacewise

full-time

Posted on:

Location Type: Hybrid

Location: Zürich • 🇨🇭 Switzerland

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Job Level

Mid-LevelSenior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformPandasPythonSQL

About the role

  • 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.

Requirements

  • 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.
Benefits
  • 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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
predictive modelingmachine learningdata analysisstatistical modelingregressionclusteringtime-series analysisdata visualizationforecastingpricing algorithms
Soft skills
communicationproblem-solvingcollaborationindependenceanalytical thinking