Ibp Data Product Owner

hace 6 meses

Barcelona, España PepsiCo A tiempo completo

Overview:
**About**
***
**D+A**
***
**in PepsiCo**

PepsiCo is using the power of data to transform the way our brands are sold every day. Our Data & Analytics group influences every aspect of how we sell and move our products. In just a short period of time, they’ve built new capabilities that have defined the data science roadmap across all of our brands. Members of our team solve complex problems facing our rapidly changing business and get to see their work come to life in the real world.

Are you interested in a career in
**Data & Analytics** in PepsiCo?

Then now is the time to explore the opportunities of PepsiCo: join us as the next
** IBP Data Product Owner.**

Working with inspiring and experienced colleagues, you'll find that the atmosphere in our office in
**Barcelona** is informal and engaging. With an active, get-things-done culture, this is a place where your dynamism and agility will make a difference.

**Your mission**:
Product Management as a stand-alone pillar within D+A was dissolved and wholly absorbed into DPS. This created a capability gap in D+A which led to a range of issues (confusion over roles/responsibilities, inefficiency, attrition of technical talent, etc.). A new Data Product Management (DPM) pillar in D+A (led by Sr. Director, Roy Chung) will fill this gap and ensure that D+A delivery capability is optimized via:

- Improved talent fit to task (e.g. Data Scientists doing data science vs. status reports)
- Clarified roles and responsibilities
- Reduction of redundancies/duplication at the onset, and
- Streamlined collaboration with both DPS, as well as broader Business partners and customers across the enterprise

**Responsibilities**:
**Your day to day with us**:
**Delivery Feasibility and Accountability**
- Manage delivery against key technical delivery milestones
- Compile and document Functional Requirements submitted by BE, DPS or Business Partner, and get estimates/feasibility assessment from data engineering
- Collaboratively manage reporting that measures D+A’s execution for IBP
- Define and drive Business Customer adoption of “acceptance criteria” for delivery from D+A

**Translation**
- Lead the “Articulation of the questions that can be answered” and address the core challenge sought to be resolved by the Business customer
- Work with engineering and data science teams to write and steward user stories and requirements in Azure DevOps
- Translate the analytics solutions back to the business to ensure its actionable and business can drive value from those insights
- Simultaneously ensure Data Engineering and Data Science teams are spending optimal time at work in their specialties while ensuring the business understands what is going to be delivered and how it solves their problem
- Communicate proactively to two audiences (Business and Technical) at once
- Ensure the technical teams are clear on the “why” from the perspective of the Business customer

**Technical Documentation and Artifacts**
- Work with multiple stakeholders to author technical data requirements for a technical audience (+ build templates of these set of Technical requirements)
- Collaboratively design and document the data product artifacts required by the project
- Ensure technical documentation is readily available for data products produced and that value is communicated to key stakeholders

**Presentation, Narrative and Adoption**
- Own presentation of DE/DS output to Business Customer, or support when presented as part of Digital Product
- Help track benefits of these insights to leadership to drive acceptance
- Collaborates with Practices (ETO, DPS, DX, VCT, etc..) for embedding analytics solutions in the business and overcoming implementation difficulties

Qualifications:
**What will you need to succeed**:

- Bachelor’s degree
- 7-10 years of Product Management, Data Analytics, Science and Management in business facing functions
- 1+ year experience in Food/Beverage/Manufacturing or Consumer Products industry
- 3+ years of experience leading/building advanced analytics and big data solutions or building enterprise SaaS
- Excellent ability to identify sources of value from data analytics across core business domains (such as marketing, risk, and operations) and to define paths realizing that value
- Familiarity with machine-learning technologies and tools, such as big data stack, Python, and visualization techniques
- Familiarity with principles and tools for data governance and stewardship
- Strong communication skills and an ability to break down complex information into relevant and digestible points for both inside D+A and externally to the business
- Excellent leadership skills, with a team-player attitude to drive the end-to-end implementation of use cases under time pressure
- Demonstrated ability to effectively communicate with all levels of the organization and solve highly complex problems across teams
- Strong people management skills with the ability to dev

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