Decision Scientist

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 - THE 3CS: CONFIDENCE, COLLABORATION AND CREATIVITY.

CONFIDENCE allows athletes to make quick decisions on the field, to reach higher. For us at adidas confidence means acknowledging that we don’t have all the answers. But we are willing to take risks, we try new things. And if we fail, then this is part of our learning - it helps us improve.

COLLABORATION. Every elite athlete relies on partners: coaches, teammates, and nutritionists. We, too, know that we are stronger together. Winning as one team takes open and candid dialogue, inclusiveness and trust in each other’s abilities and talents.

Being the best sports company in the world takes CREATIVITY. No great athlete succeeds by copying their predecessors’ training plans and strategies. We have to be open to new ideas, explore, gain an edge and stand out. Only then can we succeed.

**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- LOCATION:
- Gurgaon- TEAM:
- Digital- STATE:
- HR- COUNTRY/REGION:
- IN- CONT