Data Analyst jobs in Germany

The Data Science Consultant provides services that maximize the value of the customer’s business through data-driven insights and enhanced decision support. This role will be responsible for advising the customer and recommending software configuration alternatives and implementing the software that is configured to optimize the solution so that the customer may realize the maximum value from the software.

1. Provide analytical services as part of a team conducting proofs-of-concept and identifying opportunities to create customer value.
2. Perform data analysis to discover patterns, trends, and anomalies in customer data, translate the results into actionable insights, and present results and recommendations to support customers in improving their data quality.
3. Extract and present data stories from customer data sets to demonstrate value of solution and guide the customer in their priorities.
4. Guide the customer through identification of project success metrics.
5. Work with other members of the Blue Yonder team to understand domain issues and customer-specific requirements and translate them into model enhancement and tuning activities.
6. Build, configure and train models to support overall project objectives, and run simulations and what-if analyses to evaluate alternative scenarios.
7. Support the successful delivery of the solution to the customer by making recommendations and providing quantitative evidence of the project’s results.
8. Keep up with industry trends in data science practice and continuously improve the consulting team’s tools and methodologies.
9. Travel to customer and team work locations (according requirement, around 10%).

1. PhD and additional European language skills are a plus.
2. Graduate degree in Operations Research, Statistics, or a related quantitative field, is required, and advanced knowledge of machine learning is preferred.
3. Ability to elicit customers’ knowledge, both explicit and tacit, about business objectives, strategic concerns, and policies related to the scope and success of the project.
4. Able to translate complex data into business insights and opportunities to create value.
5. Ability to communicate analytic insights and recommendations to customers without a deep knowledge of statistics by relating data stories to business situations and processes.
6. Familiarity with business processes for retail, pricing, and supply chain management is preferred.
7. Demonstrated experience of script programming languages, preferably Python, for data analytics and machine learning applications.
8. Ability to create dashboards, visualizations, and reports to communicate statistical findings.
9. Capable of working with and selecting relevant subsets of large data sets.