Digital ID Data Analyst

Key Responsibilities

• Build & own insights & metrics requirements’ backlog across functions

• Work with business to gather insights / metrics requirements, define business logic & analyze the

data needed to build them

• Query datasets from various data sources and perform ad-hoc data analysis

• Establish partnerships with cross-functional enablers including data quality, data ingestion, and

business team members

• Perform data analysis across domains like line plan, sales orders, channels etc. to support

‘Tagging Coverage’ reporting

• Support buildout of ‘Ongoing Monitoring’ metrics to accelerate stabilization of OB scanning

capability

• Perform detailed analysis & accelerate developing of critical scanning metrics like Scan Accuracy

& GTIN / Inv accuracy

• As the Digital ID ‘data’ subject matter expert, partner with capability and analytics teams to

drive adoption of ‘item level’ data

• Support formulation of problem statement and definition of scope

• Analyze and understand root cause(s) to inform solution options

• Map business process flows (As-Is and To-Be)

• Gather feature requirements and use cases

• Inform roadmap and guide testing/validation

• Support identification of risks and mitigation approaches

• Engage with key stakeholders and super users to gather requirements and pilot/scale solutions

• Work functionally – Supply Chain, Procurement, Global Manufacturing, etc – both

with business and analytic teams

Requirements

Qualifications

• Bachelor’s Degree in computer science, MIS, analytics, other quantitative disciplines, or related

fields

• 5 years of relevant experiences in data & analytics product creation and adoption

• Strong hands on experience with SQL, Python, AWS, Snowflake, Databricks, Tableau & related

toolsets

• A strong history of supporting cross functional data product delivery teams

• Excellent communications skills (written and verbal) and strong interpersonal skills

• Understanding of data architecture, data taxonomy, and both structured and unstructured data

• Experience with agile development methodologies

• Experience with real-time data collection and processing