Data Scientist - AI & Scalable Analytics Solutions (f/m)

This role function is to help the organization scale and standardize how analytical and AI capabilities are developed, deployed, and maintained. The ideal candidate not only builds high-quality models but takes ownership of ensuring those models move into active use and continue delivering value over time. They are passionate about turning one-time analyses into repeatable, organization-wide solutions and developing tools and applications that put data-driven capabilities directly in the hands of business users. They partner closely with BI, IT, and business stakeholders to embed data-driven decision-making durably into day-to-day operations.

What You Will Do: Develop Predictive Models: Designs and implement statistical models and machine learning algorithms to analyze complex datasets and generate actionable insights.

Data Processing and Management: Collects, cleanses, and organizes large-scale data from various sources to ensure accuracy and reliability for analysis.

Communicate Analytical Findings: Presents complex data insights and technical information to stakeholders in a clear and understandable manner, facilitating informed decision-making.

Standardize Analytical Processes: Supports the development of consistent, repeatable workflows for data preparation, model development, and reporting to improve quality and reduce duplication of effort across the team.

Scale Data Solutions: Assists in transitioning analytical work from one-off analyses to scalable, reusable solutions that can be applied across multiple business areas or sites.

Support Model Deployment: Assists in moving developed models from experimentation into operational use, ensuring outputs are accessible and actionable for business stakeholders.

Document & Maintain Work Products: Maintains clear documentation of models, data processes, and analytical approaches to support knowledge sharing, continuity, and ongoing improvement.

Develop Business-Facing Tools & Applications: Builds lightweight applications and interactive tools that make model outputs and analytical capabilities accessible and usable by non-technical business users.

Translate Requirements into Working Solutions: Works with business stakeholders to understand their needs and converts those requirements into functional, user-ready data products.

Support Tool Maintenance & Iteration: Maintains and improves existing tools and applications based on user feedback and changing business needs, ensuring solutions remain accurate and relevant over time.

What You Will Need: Data Analysis: Proficient in analyzing large and complex datasets to identify trends and derive actionable insights.

Statistical Modeling: Expertise in developing and applying statistical models to support business decision-making processes.

Machine Learning: Skilled in designing, implementing, and evaluating machine learning algorithms for predictive analytics.

Programming: Advanced proficiency in programming languages such as Python and R for data manipulation and analysis.

Data Visualization: Ability to create clear and informative visualizations using tools like Tableau, Power BI, or matplotlib.

Communication: Effectively conveys complex data findings to non-technical stakeholders in a clear and understandable manner.

Business Acumen: Understands key business drivers and aligns data science projects with organizational goals and strategies.

Data Management: Knowledgeable in data warehousing, data cleaning, and database management to ensure data integrity and accessibility.

Process Standardization: Ability to develop and follow consistent, repeatable approaches to data preparation, analysis, and model development that improve team efficiency and output quality.

Scalability Awareness: Understanding of how to design analytical solutions that can grow with the business, moving beyond one-time analyses toward reusable, maintainable work products.

Cross-Functional Integration & Partnership: Ability to connect data science outputs to the systems and workflows used by other teams, working effectively with IT, operations, and business stakeholders to ensure insights translate into day-to-day operational action.

Documentation & Knowledge Sharing: Skilled in clearly documenting processes, models, and methodologies to support team continuity and organizational learning.

Application Development: Ability to build functional, user-facing tools and applications that package analytical or ML capabilities for business use.

User-Centered Thinking: Designs solutions with the end user in mind, ensuring tools are intuitive, practical, and solve real business problems.

Iterative Development: Comfortable building, testing, and refining solutions based on stakeholder feedback rather than waiting for a perfect first release.

What You Will Gain: Advancement opportunities in international team

A total rewards package, that includes: private health insurance, life & accidental insurance

Multisport package

Meal Vouchers

Company performance bonus program

Work‑life balance, semi‑flexible working time

PPK: company offers payment to your PPK account up to 4% of your compensation depending on seniority

Hybrid work model

Relocation & Educational support