Engineering
English, German
About the company
Meaningful solutions can only be achieved through deep inquiry and understanding. Sustainable change can only be accomplished with the specialist knowledge of what is truly beneficial to your company's future success. We are thinkers and builders; we are fueled by curiosity.
Data Scientist with analytical mind, visionary power and implementation strength to help AI-based business models succeed.
Data is the foundation of AI-based business models, products and services. The key to success is to analyze an efficiently collected database wisely, to sketch possible solutions from it, to provide proof of feasibility and to implement the ideas with determination. If this applies to you and you are looking forward to shaping the future of AI-based products and services as a team player with data, AI and domain experts from various fields, then you have come to the right place.
Job Description
Use data to improve business decisions, enhance customer satisfaction and/or increase business impact.
Perform data preprocessing, determine appropriate analytical approaches and modeling techniques and deploy a variety of supervised and unsupervised machine learning models (e.g. deep learning, NLP, clustering), recommendation systems or similar.
Create insightful visualizations and deliver presentations e.g. to business stakeholders telling convincing & logical stories using data.
Be a proactive contributor to collection of best practices in Data Science and Machine Learning (e.g. for model comparison) and development of Sclable’s Data Science roadmap.
Stay up-to-date on data science and machine learning developments & trends.
Collaborate with data engineers, machine learning engineers, UI/UX designers and other stakeholders in continuously optimizing the service delivery method.
Requirements
At least 3 years of applied Data Science experience analyzing data, building production-grade AI/ML models and telling stories with data with positive business impact.
Advanced data analytics skills and experience building beautiful data visualizations (e.g., Power BI, Shiny).
Profound statistical and mathematical understanding acquired through academic studies (e.g., Data Science, Mathematics, Statistics, Computer Science).
Proficiency in programming in an OOP (preferably Python) required, additionally in R is a plus.
Excellent know-how of Data Science and Machine Learning packages and tools (familiarity with TensorFlow, Keras, PyTorch is a plus).
Hands-on experience with Big Data environments and tools (e.g., Spark, Databricks) in a Cloud setting (e.g., Azure, AWS, GCP) with ability to use them for developing, training, testing and deploying ML models.
Strong communicational skills to work effectively with stakeholders on different levels (incl. management) and with different experience in terms of data literacy.
Team player with hands-on mentality focusing on customer satisfaction.
As a plus: Track record in data collection, processing, cleansing and storage as a Data Engineer.
Benefits
new way of thinking and working, agile team of experts, Open communication, flat hierarchy, plenty of individual responsibility, opportunity to keep evolving rapidly in diverse and challenging projects
The gross monthly salary starts at € 3.300 (according to the collective agreement for data processing and information technology) and, depending on qualifications and experience, usually ranges around € 3.900; in the case of special qualifications, we are also prepared to negotiate beyond that.