Senior Data Analyst, Customer Experience & AI (Remote)

Dan.com - a GoDaddy brand; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote US work arrangement

12-month contract with extension

Medical, dental, vision, and life

Job summary

Dan.com - a GoDaddy brand is seeking a senior data analytics professional to lead analysis across customer journey data. You will apply SQL, Python or R, and ML/NLP techniques to identify trends and enable improvements.

The role requires cross-functional collaboration and the ability to translate complex data into actionable insights. The position emphasizes developing KPI scorecards, integrating feedback with operational data, and presenting results to stakeholders.

Qualifications

• Degree in analytics or a quantitative field.
• 8+ years of data analytics experience.
• 2+ years in CX, support, or marketing analytics.
• Strong SQL and Python/R skills.
• Experience with predictive analytics or ML techniques.
• Experience with Generative AI and AI tools preferred.

Responsibilities

• Analyze large datasets with SQL, Python, or R and identify trends.
• Synthesize surveys and analytics across the customer journey.
• Apply ML, NLP, and statistical methods to customer conversations and tickets.
• Develop customer segmentation and KPI scorecards.
• Integrate feedback with operational data to drive actions.
• Present findings to stakeholders and drive improvements.

Skills

SQL

Python

R

Data analysis

Stakeholder communication

Cross-functional collaboration

Education

Bachelor's degree

Master's or Ph.D. (quantitative field)

Tools

Pandas

scikit-learn

TensorFlow

PyTorch

Job description

Dan.com - a GoDaddy brand is seeking a senior data analytics professional to lead analysis across customer journey data. You will apply SQL, Python or R, and ML/NLP techniques to identify trends and enable improvements.

The role requires cross-functional collaboration and the ability to translate complex data into actionable insights. The position emphasizes developing KPI scorecards, integrating feedback with operational data, and presenting results to stakeholders.