Data Scientist lead

Robotic Process Automation LLC; Seattle (WA); On-site; USD 120,000 - 170,000; Full time

Job summary

Robotic Technologies Automation is seeking a data engineer/data scientist to validate scores against outcomes like churn, and to build large-scale Databricks pipelines. You will identify and fix data quality issues before leadership sees results, document methodology and data lineage, and explain findings to non-technical executives.

The role requires strong Python/PySpark, SQL, and Databricks optimization skills, plus a skeptical, detail-oriented approach and solid documentation practices.

Qualifications

• Proficient in Python/PySpark and SQL for large-scale data work.
• Experience with Databricks and performance tuning (partitioning, Delta, cluster sizing).
• Applied statistics for predicting churn and related metrics.
• Use Git for version control and maintain production-grade code quality.
• Demonstrated habit of validating results and avoiding overconfident claims.
• Strong documentation and organizational discipline.

Responsibilities

• Validate scores 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

Applied statistics

Git/version control

Production-quality coding

Data quality checks

Documentation

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.