Senior Data Scientist

TL;DR

Senior Data Scientist (Data Science/ML): Own the science and engineering behind hirify.global's measurement pipeline for ad impact, with an accent on causal inference, selection-bias reduction, and privacy-preserving cleanroom execution. Focus on translating statistical and ML methodologies into scalable PySpark/SQL production workflows, validating correctness with rigorous data quality checks, and auditing model outputs across large, disparate datasets.

Location: San Francisco

Salary: $130,000–$196,500 (annual base compensation range)

Company

hirify.global is a data collaboration platform focused on privacy-preserving identity and building a connected customer view.

What you will do

• Design, develop, and maintain statistical and ML-based measurement models that run at scale in privacy-preserving clean rooms.
• Translate measurement methodology into configuration-driven production pipelines using PySpark and SQL, ensuring correctness via data quality checks and invariant validation.
• Prototype new statistical and data modeling frameworks from exploratory research through production-ready workflows with strong reproducibility and code quality.
• Apply causal inference and bias correction to reduce selection bias, build representative samples, and analyze randomized and observational studies.
• Integrate measurement models into cloud-based data infrastructure and troubleshoot end-to-end automated pipeline failures.
• Validate and audit model outputs across large datasets, diagnose anomalies, and document methodology and operational runbooks.

Requirements

• Master’s with 5–8+ years experience or PhD with 2+ years experience in a data science-related field (e.g., statistics, mathematics, computer science, engineering, economics).
• Strong proficiency in Python (pandas, PySpark) and SQL for large, complex datasets in distributed environments.
• Solid statistical foundation (regression, classification, time-series, sampling, selection bias correction) and hands-on experiment design (A/B, holdout, geo-tests) with causal inference methods.
• Experience with modern data/analytics frameworks (Spark, Jupyter, Airflow) and cloud environments (AWS or GCP), plus comfort with git and command-line interfaces.
• Experience building, prototyping, and productionizing statistical/ML models by translating research into maintainable production workflows.
• Ability to communicate complex measurement insights to technical and non-technical stakeholders and collaborate across data/software/product teams.

Nice to have

• Familiarity with privacy-preserving data environments (clean rooms, k-anonymity, aggregation thresholds).
• Experience in adtech/martech/digital marketing analytics (attribution, ROAS, conversion modeling, identity resolution).
• Experience with retail/CPG data and privacy-preserving measurement across transaction-level datasets.

Culture & Benefits

• Flexible paid time off, paid holidays, options for working from home, and paid parental leave.
• Comprehensive benefits package including medical, dental, vision, life and disability, and an employee assistance program.
• 401(k) matching plan (1:1 match up to 6% of salary) and an Employee Stock Purchase Plan with a 15% discount.
• Collaborative environment with in-person and virtual events.

Hiring process

• Interviews focused on technical depth in measurement modeling, causal inference, and production pipeline implementation.
• Discussion of collaboration and communication with technical and non-technical stakeholders.