Senior Data Scientist (SaaS)

TL;DR

Senior Data Scientist (SaaS): Building and deploying machine learning models to predict sales outcomes, customer churn, and revenue projections with an accent on sales performance optimization and forecasting. Focus on developing predictive models using time series and regression, implementing A/B testing, and integrating AI insights into Power BI dashboards.

Location: Hybrid (Brno, Czech Republic or Slovakia)

Company

Global provider of BIM design software for the AEC industry, part of the Nemetschek Group.

What you will do

• Build, validate, and deploy ML models to predict sales outcomes, customer churn, and revenue projections.
• Implement A/B testing frameworks and statistical analysis to evaluate the effectiveness of sales strategies.
• Develop predictive models for sales forecasting using time series, regression, and classification algorithms.
• Create interactive Power BI reports and dashboards that integrate AI insights and predictive model outputs.
• Collaborate with sales leadership and BI teams to translate complex technical findings into actionable business narratives.
• Manage the machine learning lifecycle (data prep, training, deployment) within the Microsoft Fabric platform.

Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• 5-7 years of professional experience in data science or analytics, preferably within a software/SaaS environment.
• Advanced proficiency in Python (pandas, scikit-learn, TensorFlow/PyTorch) and strong SQL skills.
• Expertise in Power BI for creating interactive dashboards and reporting.
• Solid foundation in statistics, experimental design, and MLOps practices (model monitoring, deployment pipelines).
• Fluency in English is required; German is a plus.

Culture & Benefits

• Comprehensive onboarding and ongoing professional development opportunities.
• Clear paths for career advancement within sales and other departments.
• Collaborative, innovative, and supportive team environment.
• Competitive compensation with performance-based incentives.
• Flexible work arrangements, including options for remote work.