General Purpose
As a Decision Scientist you will apply the full analytics toolkit to deliver analytics solutions on a variety of topic (i.e. members’ lifecycle management, consumer engagement, digital marketing and business performance), to enable make fact-based decisions across adidas sales channels. You will hold the business accountable that data capabilities are being used to drive value. You will translate insights into actions that drive strategic and operational decisions across adidas sales channels.
Key Responsibilities
Consulting
- Partner with our business teams to make well-informed decisions backed by cross- channel sales data.
- Apply expertise in data analytics and statistics to answer key business questions.
- Focus on understanding and analyzing data from the past and present perspectives to produce reliable insights for our stakeholders.
- Translate data insights into actions and recommendations that will drive membership consumer engagement and other key sales initiatives.
- Empower the business to use data with confidence through upskilling and self-service capabilities.
- Support in the process of problem framing, formulating hypotheses and the decision-making parameters. Defining the appropriate data points required to support effective decision making.
Analytics / Reporting
- Develop quantitative analysis, tools, ad hoc reports and models to support decision making. Analysis areas might include (but not limited to): members’ lifecycle management, consumer engagement, digital marketing and business performance.
- Produce meaningful data visualization such as charts, infographics and dashboards to communicate findings and actionable recommendations to internal stakeholders clearly and effectively.
- Work as part of Agile product teams (e.g. Scrum / Kanban) to deliver business value.
Requirements, Education & Professional Experience
- A degree in mathematics, economics, statistics, computer science or a similar quantitative field.
- 5+ years of experience in data analytics, data modelling, decision science or a similar function, applying experimentation methods to test various hypotheses for generating consumer / product / marketing / business insights and influencing data-driven decision making.
Hard-Skills
- Experience finding, cleaning and transforming large data sets to build reports, dashboards and / or data assets.
- Statistical modelling and data analysis experience (e.g. significance testing, regression modelling, sampling theory etc.) and knowledge of linear algebra, calculus, probability and statistics.
- Experience using Python, R or a similar scripting language for statistical modelling. Extensive knowledge of packages such as NumPy, Pandas etc. Knowledge of Spark would be an added advantage.
- Experience with SQL (e.g. aggregate functions, joins) NoSQL or other data querying languages.
- Good data visualization skills e.g. Tableau, MicroStrategy, Power BI, matplotlib, plotly or something similar.
- Experience working with tech teams e.g. IT, data science and data governance.
- Basic understanding of machine learning / deep learning would be a plus as well.
- Comfortable working with enterprise-level platforms and technologies e.g. databricks.
- Experience applying decision framing and hypothesis design techniques to break down complex problems into manageable choices and map decision processes.
- Experience with decision and data modelling to support decision-making under uncertainty at individual and organizational level.
- Ability to conduct risk and tradeoff analytics to support informed decision making under ambiguity.
- Ability to communicate data insights effectively through compelling visual and verbal storytelling.
- Fluent in English both verbally and written.
Soft-Skills
- Demonstrates agility by staying open to change, learning quickly and shifting perspectives to respond effectively to new challenges and environments.
- Applies structured problem framing and solving techniques to define clear and actionable problem statements.
- Experience communicating with cross-functional business stakeholders including product experience, strategy & innovation, markets, digital growth etc.
- Good communication skills, comfortable presenting complex topics in a clear and understandable way.
- Clear written and oral communication skills.
adidas celebrates diversity, supports inclusiveness and encourages individual expression in our workplace. We do not tolerate the harassment or discrimination toward any of our applicants or employees. We are an equal opportunity employer.