Data Scientist lead

Quantum Technologies LLC; Seattle (WA); On-site; USD 120,000 - 160,000; Full time

Job summary

Quantum Technologies LLC in Seattle, WA is seeking a data scientist/engineer to validate scoring models and link outcomes like churn to business metrics. You will build and optimize large-scale data pipelines in Databricks, ensure data quality, and document data lineage and modeling logic for leadership review.

The role requires strong Python/PySpark, SQL, and statistical modeling skills, with a focus on robust production-grade coding, reproducibility, and clear communication to both technical

Qualifications

• Python/PySpark and advanced SQL
• Databricks performance tuning for partitioning, Delta, and cluster sizing
• Applied statistics, especially predictive modeling for yes/no outcomes like churn
• Git/version control and production-quality coding habits
• Habit of checking whether results make sense; skeptical of results that look too good
• Strong documentation and organizational discipline

Responsibilities

• Validate the score against customer outcomes such as churn and care contacts
• Build and optimize large-scale data pipelines in Databricks
• Catch and fix data quality issues before results reach leadership
• Document methodology, data lineage, and logic changes
• Explain findings to non-technical and executive audiences

Skills

Python/PySpark

Advanced SQL

Databricks tuning

Applied statistics

Git version control

Data quality checks

WoE/IV experience

Documentation discipline

Tools

Databricks

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization

US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description

• Validate the score against customer outcomes such as churn and care contacts
• Build and optimize large-scale data pipelines in Databricks
• Catch and fix data quality issues before results reach leadership
• Document methodology, data lineage, and logic changes
• Explain findings to non-technical and executive audiences

Must-haves

• Python/PySpark and advanced SQL
• Databricks performance tuning (partitioning, Delta optimization, cluster sizing)
• Applied statistics, especially predictive modeling for yes/no outcomes like churn
• Git/version control and production-quality coding habits
• Habit of checking whether results make sense as they work; skeptical of results that look too good
• Strong documentation and organizational discipline

Strong preferences

• Weight of Evidence/Information Value (WoE/IV) experience
• Wireless or telecom network KPI knowledge

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.