Sr. Data Analyst

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCo’s global business scale to enable business insights, advanced analytics and new product development. PepsiCo’s Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations, and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation.

What PepsiCo Data Management and Operations does:

• Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company
• Responsible for day-to-day data collection, transportation, maintenance/curation and access to the PepsiCo corporate data asset
• Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders
• Increase awareness about available data and democratize access to it across the company

Job Description
As a member of the data engineering team, you will be the key domain expert overseeing PepsiCo's business process and drive a strong discussion for how Supply Chain, Financial, Consumer, Channel, Category business needs to be defined and prioritize by working very closely with business leads, data science team and data engineering team. You'll develop an in-depth understanding of business processes in and translate business requirements to data engineering team in technical way.

Accountabilities

• Discover, analyze, and scope data requirements & representing them in conceptual and logical data models
• Gather and analyze data pertaining to various business processes such as forecasts, capital requirements, inventory, logistic, manufacturing and production capacity to develop supply chain models. geographics, POS, pricing and promotion, store profile, e-commerce data to develop channel models.
• Create high-level process models (system interface diagrams, workflow & swim lane diagrams, data flow diagrams) to represent processes for the area under analysis
• Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.
• Responsible to improve the quality of data in relation to defined expectations
• Perform analysis of system data to identify patterns, exceptions, and erroneous data

Qualifications/Requirements

Qualifications

• 6+ years of experience with data analysis & data profiling in project, business requirements definition or data engineering in CPG or Manufacturing Industry.
• 5+ years’ work experience in the areas of Distribution Network Analysis, Manufacturing, Production Network Optimization, Transportation, Demand Planning, or other areas related to Supply Chain or other domains such as Financial, Consumer, Channel, Category etc.
• 4+ years of strong Data Profiling experience & ability to identify trends and anomalies in the data to in-form data model build out.
• Experience in working with Datasets from POS Aggregators such as IRI, Nielsen, Kantar etc.
• Experience working with structured/unstructured datasets, ability to clearly document and communicate requirement to technical team members.
• Experience with Business Intelligence tools, SQLTools.

Education

• Bachelor’s Degree in Supply Chain and/or Operations Management is Required, Masters Preferred.

Competencies

• Strong knowledge and understanding of Supply Chain data elements and processes per the necessary in-scope data domain (i.e., Customer, Material, Vendor)
• Ability to translate business requirements into critical data dependencies and requirements
• Able to challenge and align various stakeholders to a common set of standards
• Self-starter with excellent written & verbal communication skills.
• Self-learner and eager to understand data, business processes, concepts, and technologies.