Consumer Analytics Manager

hace 4 semanas

Miguel Hidalgo, México PepsiCo A tiempo completo

**Responsibilities**:
**Are you looking for a challenging opportunity in an organization with a dynamic, innovative, and diverse environment? if so, your future is at PepsiCo.**

PepsiCo products are enjoyed by consumers more than one billion times a day in more than 200 countries and territories around the world. PepsiCo generated more than $79 billion in net revenue in 2021, driven by a complementary beverage and convenient foods portfolio that includes LAY’S ®, DORITOS ®, CHEETOS ®, GATORADE ®, PEPSI ®, QUAKER ® and more. PepsiCo's product portfolio includes a wide range of enjoyable foods and beverages, including many iconic brands that generate more than $1 billion each in estimated annual retail sales.

Guiding PepsiCo is our vision to Be the Global Leader in Beverages and Convenient Foods by Winning with PepsiCo Positive (pep+). pep+ is our strategic end-to-end transformation that puts sustainability and human capital at the center of how we will create value and growth by operating within planetary boundaries and inspiring positive change for planet and people.

Our employees drive our culture. No two days are the same; we are dynamic and full of passionate teams that embrace new ideas through our collaborative spirit. At PepsiCo, we know that our company can only succeed when our associates and the society we serve flourishes. We are committed to fostering a diverse workforce by creating a collaborative, equitable and inclusive space where everyone, regardless of what we look like, where we come from or who we love, has a voice. At PepsiCo we create a Space to be y( )u.

Currently we are looking for our next:
**Consumer Insights Manager**

**Which is the main objective of this role?**

Product Owner of Revenue Management Advanced Analytics platform leading multifunctional teams from Revenue, IT, Sustain, GBS and Analytics to deploy descriptive and Predictive dashboards defyning pricing strategies and portfolio assortment across sector within all food categories while leading and deploying Artificial Intelligence and machine learning models for next gen Revenue implementations to maximize sales and Marginal Contribution ROI

**What will you be doing?**
- Lead and manage the MLOps team, overseeing the end-to-end operationalization and deployment of machine learning models.
- Collaborate with data scientists, machine learning engineers, and cross-functional teams to develop efficient machine learning workflows and processes.
- Design, implement, and maintain scalable infrastructure and platforms for deploying, monitoring, and managing machine learning models.
- Implement best practices for model versioning, reproducibility, and documentation to ensure traceability and compliance.
- Develop and maintain automated pipelines for model training, evaluation, and deployment using tools such as RStudio Connect, Docker, and orchestration frameworks.
- Work closely with IT and DevOps teams to ensure the proper integration of machine learning solutions with existing infrastructure and deployment processes.
- Implement monitoring and alerting systems to proactively detect model performance issues, data drift, and anomalies in production.
- Collaborate with data engineering teams to ensure efficient data ingestion, storage, and processing for machine learning workflows.
- Stay updated with the latest trends, tools, and technologies in MLOps, and drive the adoption of new techniques to improve efficiency and scalability.
- Provide technical guidance and mentorship to the MLOps team, fostering a culture of learning, collaboration, and innovation.
- Collaborate with stakeholders to communicate and present MLOps-related findings, insights, and recommendations in a clear and impactful manner.

Qualifications:
**Who are we looking for?**
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field. A Ph.D. is a plus.
- Proven experience as an MLOps Manager or similar role, leading teams in operationalizing machine learning models.
- Strong expertise in machine learning, including hands-on experience with frameworks such as Keras and scikit-learn.
- Proficiency in using RStudio Connect for deploying and managing machine learning models in production.
- Experience with containerization technologies like Docker for packaging and deploying machine learning models.
- Solid understanding of MLOps best practices, including model versioning, reproducibility, monitoring, and documentation.
- Strong programming skills in languages such as Python and R.
- Experience with orchestration frameworks (e.g., Kubernetes, Apache Airflow) and infrastructure-as-code tools is a plus.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and data engineering technologies (e.g., Spark, Hadoop) is a plus.
- Excellent problem-solving skills and the ability to work in a fast-paced and dynamic environment.
- Strong communication and leadership skills, with the ability to effectively collaborate with stakehol

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