General information

All posting locations: Remote, Pennsylvania, United States of America

Job Function: 04 - IT

Date Published: 28-Dec-2022

Ref #: R-63357

Base Salary Range: $ - $

Target Total Cash Range*: $ - $

Target Total Cash*: *Target total cash represents this role's annualized cash earning potential at target (base salary + target bonus). Target total cash is contingent on targeted company performance achievement and individual attainment of performance goals. Therefore, target total cash is not guaranteed earnings.

Compensation Disclaimer: The compensation offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors.

Description & Requirements

The Machine Learning Operations (MLOps) is a new team and is instrumental in guiding the Advanced Analytics journey at Kraft Heinz. As a part of this highly energetic team you will be responsible for creating/maintaining model pipelines and putting models into production. You will also get opportunities to expand your horizons working with the data scientists to develop ML models and best in class architecture using industry best practices.  Overall- if you are passionate about applying technology to solve practical business problems- developing intelligent tools- and working with a friendly team to drive business value- this is going to be your dream team to enrich your career.  The sky is not the limit in terms of enhancing your knowledge and working on a variety of projects with the Data Science team at Kraft Heinz!

Primary Responsibilities

• Implement machine learning algorithms and customized libraries
• Assist Data Science team with development of complex tools- models or database builds
• Collaborate with data engineers and data scientists to develop data and model pipelines
• Improve existing Machine Learning models
• Write production-level code
• Bring code to production and engage in code reviews
• Use of problem-solving- advanced Analytics methodologies (ML/AI) knowledge to derive architecture of ML models and assist development of new models
• Responsible for ongoing operation for existing models.
• Working with Data Engineers & Data Scientists to ensure integrity & governance- rituals and routines
• Provide inputs/stories and assist in prioritization of Data Engineering sprints

Qualifications

• Understanding of the major modelling techniques are how to apply them (Linear and Logistics Regression- Bayesian- Time series- Confidence interval- Deep Learning etc.)
• Experience in role delivering and supporting analytical capabilities.
• Experience supporting ML models in a production cloud environment (Azure experience preferred)
• “Hands-on” experience with analytical tools (preferably AzureML- Vertex- SageMaker- Snowflake- DataBricks- Tableau- Alteryx- SQL- Python- and/or R)
• Strong experience developing CI/CD pipelines
• Fluent in version control tools and practices (Github- Azure DevOps).
• Project management experience and strong communication skills
• Self-Starter- driven with high business process acumen
• Team Player with a positive attitude and ability to work across different business stakeholder and technical teams to accomplish complex tasks
• Experience working with database systems and analytical tools
• Strong communication- problem-solving skills and a strong team player

Domain Expertise

• Working experience in supporting mission critical ML loads in a production environment.
• Proven model operation management (production rollouts- upgrades- security) experience
• Experience leading analytical innovation

Experiences

• Experience in leading and managing cross functional teams.
• Expert at developing analytical talent and managing remote teams (internal and external)

Individual Skills

• Strong leader- collaborator- team player- and individual contributor