Data Analyst
vor 2 Monaten
As a Data Scientist at Adidas, you will play a key role in driving business growth through data-driven insights and strategic decision-making.
Key Responsibilities:- Develop and apply advanced analytics methodologies to optimize customer acquisition, engagement, conversion, experience, and loyalty.
- Contribute to the generation of insights to increase understanding of adidas consumers, exploring their affinities and intents, to make recommendations to individual consumers through the right digital channel at the right time.
- Continuously improve our way of working by refining methodologies, challenging the status quo, and raising standards for faster delivery.
- Support improvement and automation of the data science platform and machine learning pipeline to facilitate data science activities and serve near real-time use cases.
- Prepare coaching sessions for colleagues in state-of-the-art analytic techniques, data science, data engineering, data governance, and software development.
- Prepare analysis results and insights to be presented to colleagues at all levels, in a way that allows them to understand the value of your work, apply your output, and realize business potential.
- Support the development of customer segmentations, acquisition and retention strategies, predictive modeling, customer lifetime value metrics, and marketing effectiveness measures.
- University degree in a numeric/statistical discipline (M.Sc. or PhD)
- 5+ years of experience in analytics in a Digital and/or eCommerce environment, strong knowledge of the digital industry (products, technologies, solution providers, commercial models, trends)
- 3+ years of professional experience in an international & cross-functional environment
- Experience in managing a team is a plus
- Good communication skills, comfortable presenting complex topics to stakeholders at various organizational levels both in person and remotely
- Good interpersonal skills, good leadership skills
- Proven team player that can collaborate across functions and organizations
- Strong coding skills using common data science toolkits
- Strong knowledge in applied statistics, distributions, statistical testing, data mining, and machine learning algorithms
- Experience with NoSQL databases
- Experience on data aggregations, data models, and operationalization of data mining algorithms
- Experience in developing Customer profiles, CLTV, attribution model, lookalike modeling, clustering, and classification and segmentation models on large and sparse data sets
- Fluent English both verbally and written
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