Data Scientist

A fast-growing company addressing some of the world's most pressing global challenges and continues to develop new solutions is looking for a Data Scientist. The selected candidate will actively participate in the implementation of a software ecosystem. The XETR-listed company uses statistical modeling, exploratory data analysis, data visualization, and machine learning to drive analytics-driven decisions. They have managed to raise more than €2.5bn in funding so far.

Job Responsibilities:

• Create production-ready statistical and machine learning models for projecting sales at the SKU and retailer level using large-scale information
• Design new data sources, develop and test model modifications, execute computational experiments, and fine-tune model parameters for new models to improve on existing machine learning approaches
• Develop and deploy analytical models for brand and key retailer statistical sales forecasts
• Provide data-driven recommendations while working with cross-functional teams to create and deploy models and improve analytical solutions
• Communicate complex technical concepts and nuanced insights to a wide range of audiences
• Create data pipelines that transform raw data into aggregated data that may be utilized to generate signals
• Extract, Transform, and Load (ETL) in cloud data platforms 
• Produce and recognize inventive, workable solutions to business issues and difficulties to break established thought patterns
• Ensure solid plans, review sales performance, insights data, major initiatives, and new item releases with the brand and customer teams

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 3+ years of relevant experience as a software engineer
• Prolific skills working with Python
• Extensive experience with databases like SQL
• Prolific experience with exploratory data analysis, data visualization, statistical analysis, and the creation and implementation of machine learning models
• Experience with major machine learning tools and libraries
• Advanced computer literacy abilities, particularly in Microsoft Excel and PowerPoint, are necessary
• Experience or understanding of common ML-Ops patterns is nice to have
• Experience with full-stack development and time series forecasting is desirable
• Good verbal and written communication skills
• Nice to have some prior experience in the application of syndicated databases (IRI, Nielsen, and LiveRamp)
• Experience working with cloud-based data and analytics platforms, standard business intelligence dashboards, and data enrichment techniques is desirable
• Nice to have some experience with robust analytical capabilities across a variety of data sources and platforms