Decision Scientist

Decision Scientist- Area: Digital
Job family: Decision Science
GSMS Grade: M4
Number of Personnel Managed:
- Cost Center/Budget and/or Revenue Responsibility: tbd- Department: [name of department]
Direct Reporting Line: [title of reporting mgr.]
Indirect/secondary reporting line: [(title of secondary reporting mgr.)]
Subsidiary/country: [(subsidiary), country]
Location: [city]- General Purpose
Key Responsibilities
Consulting
Partner with our business teams to make well-informed decisions backed by Digital data.
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, digital growth, and other key 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 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.
- „If required“ Responsibilities- Product Ownership
Specify the product vision and roadmap as well as user stories for respective data product.
-Drive the evolution of the product, prioritize the items in your product backlog. Specify the definition-of-done in cooperation with the product team(s).
-Foster a strong relationship with key stakeholders to ensure that their views and requirements are captured in the product backlog.
-Design, manage and analyze product tests to understand optimization opportunities.
-Understand the project requirements to select appropriate approach to deliver the product.
- Requirements
Education & Professional Experience
A degree in mathematics, economics, statistics, computer science or a similar quantitative field.
Hard-Skills
Experience finding, cleaning and transforming large data sets to build reports, dashboards and / or data assets.
-Statistical modeling and data analysis experience (e.g. significance testing, regression modeling, sampling theory etc.) and knowledge of linear algebra, calculus, probability and statistics.
-Experience using Python, R or a similar scripting language for statistical modeling. 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.
-Fluent in English both verbally and written.
- „If required“ Responsibilities (Product Ownership)
Expert knowledge of Agile working methods e.g. Scrum/Kanban
- Soft-Skills
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.

AT ADIDAS WE HAVE A WINNING CULTURE. BUT TO WIN, PHYSICAL POWER IS NOT ENOUGH. JUST LIKE ATHLETES OUR EMPLOYEES NEED MENTAL STRENGTH IN THEIR GAME. WE FOSTER THE ATHLETE’S MINDSET THROUGH A SET OF BEHAVIORS THAT WE WANT TO ENABLE AND DEVELOP IN OUR PEOPLE AND THAT ARE AT THE CORE OF OUR UNIQUE COMPANY CULTURE: THIS IS HOW WE WIN WHILE PLAYING FAIR.

COURAGE: Speak up when you see an opportunity; step up when you see a need..

OWNERSHIP: Pick up the ball. Be proactive, take responsibility and follow-through.

INNOVATION: Elevate to win. Be curious, test and learn new and better ways of doing things.

TEAMPLAY: Win together. Work collaboratively and cultivate a shared mindset.

INTEGRITY: Play by the rules. Hold yourself and others accountable to our company’s standards.

RESPECT: Value all players. Display empathy, be inclusive and show dignity to all.

**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.**

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- JOB TITLE:
- Decision Scientist- BRAND:
- adidas- LOCAT