Data Science Consultant

hace 1 mes

Barcelona, España Blue Yonder A tiempo completo

· Data Science ConsultantOther Comparable titles:· Data Scientist, Data Science EngineerOverview & Scope:· Leading AI-driven Global Supply Chain Solutions Software Product Company and one of Glassdoor's "Best Places to Work"· We are seeking a highly skilled and motivated Data Science Consultant to join our Supply Chain Management team. The ideal candidate will leverage data-driven insights to optimize supply chain processes, improve decision-making, and drive business results. You will work closely with cross-functional teams, utilising advanced data analytics, machine learning, and optimization techniques to enhance supply chain efficiency, forecast demand, and solve complex operational challenges.What you'll do:· Data Analysis & Modeling: Analyze large, complex data sets related to demand forecasting, supply planning to uncover actionable insights.· Machine Learning: Apply statistical and machine learning techniques to forecast demand which would include· Data ingestion, data visualisation and insights, verifying the integrity of data used for analysis· Feature engineering, configuring forecasting models· Fine tune data attributes used in the forecasting model· Present results in a clear manner, make the complex look simple· Supply Chain Optimization: Implement optimization algorithms to improve supply chain efficiency, reduce costs, and enhance service levels.· Consulting & Advisory: Serve as a subject matter expert (SME) for supply chain analytics using data to advise stakeholders on best practices, tools, and strategies for effective supply chain management.· Process Improvement: Identify inefficiencies within the supply chain and recommend data-driven strategies for continuous improvement.What we are looking for:· Educational Background: Master's degree in Data Science (Batchelors considered with experience), Computer Science, Industrial Engineering, Operations Research, Supply Chain Management, or a related field.· Experience: 5-12 years of experience in data science or Supply Chain Operations Analytics, or worked on forecasting projects leveraging statistical/ML models; experience with data visualization tools· Technical Skills: Proficiency in data science tools and programming languages such as Python, R, SQL, and experience with supply chain management platforms/processes. Good, applied statistics skills, such as distributions, statistical testing, regression, etc· Machine Learning: Hands-on experience with machine learning techniques/algorithms (e.g., regression, classification, clustering, time series) and optimization models.· Industry Knowledge: Familiarity with supply chain processes such as demand forecasting, inventory management, procurement, logistics, and distribution.· Analytical Thinking: Strong problem-solving skills with the ability to analyze complex data sets and translate insights into actionable recommendations.· Personal competencieso Ability to work independently and as part of a team in a consulting environment.o Attention to detail, with the ability to manage large data sets and complex analysis.o Communication: Excellent verbal and written communication skills to present findings clearly to non-technical stakeholders.Our ValuesIf you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core ValuesDiversity, Inclusion, Value & Equity (DIVE) is our strategy for fostering an inclusive environment we can be proud of. Check out Blue Yonder's inaugural Diversity Report which outlines our commitment to change, and our video celebrating the differences in all of us in the words of some of our associates from around the world.All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.SummaryLocation: Warsaw; Barcelona; MadridType: Full time

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