Das ist der Job
Requirements Strong foundation in mathematics including linear algebra, probability & statistics.
Darum lohnt es sich
Build, test, and maintain analytical models for demand forecasting, price sensitivity, and promotion performance with guidance from senior team members. Collaborate with cross-functional teams to implement and scale data solutions, and communicate findings through clear analysis and visualizations.
Responsibilities Support the development of data-driven features for pricing and promotion strategies to improve revenue and profitability. Apply data science, data analysis, machine learning, and statistical techniques to help solve retail business problems such as forecasting accuracy and promotion effectiveness.
Analyze structured and unstructured retail data to identify trends, understand customer behavior, and generate actionable insights.
Solid understanding of hypothesis testing, regression analysis, and core machine learning algorithms, with at least 2 years of hands-on experience with Python(pandas, NumPy, OOP), as well as with scikit-learn or similar machine/Deep learning open-source software libraries. 2+ years of experience in data analysis using SQL and Python, including data extraction, data preparation, EDA, and basic statistical analysis. 1+ years of experience in retail or CPG, with proven expertise in price elasticity modeling, demand forecasting, promotion optimization, pricing and other retail strategies. 1+ year of experience with MLOps (Databricks, Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning, or similar), and CI / CD pipelines. 1+ year of experience in developing, integrating, delivering, and supporting AI and analytics solutions, with exposure to pricing optimization and retail analytics.
Exceptional communication and presentation skills, capable of conveying complex insights clearly and effectively to both technical and non-technical audiences. #J-18808-Ljbffr
