Senior Analytics Engineer/Data Scientist (AI)

Location: Hybrid, based in the San Francisco office 3 days per week; exceptionally qualified candidates in other US locations may be considered case by case. No visa sponsorship or relocation assistance.

Salary: $218,000–$240,000 base compensation annually, plus potential equity. A San Francisco compensation range of $205,000–$249,000 USD is also listed.

Company

hirify.global develops an AI Time platform using machine learning to capture, analyze, and optimize work time for professional services firms, including accounting and law firms.

What you will do

• Run recurring ROI analyses and build repeatable SQL/Python and pandas automation with scheduling, alerts, anomaly checks, and orchestration tools such as Airflow.
• Define core metrics and create reusable SQL data models as the analytics source of truth.
• Partner with the CX team to quantify and communicate customer ROI, prepare executive-ready materials, and participate in customer-facing presentations.
• Build customer-facing ThoughtSpot dashboards and turn analysis into concise, actionable insights.
• Improve data quality through validation tests, monitoring, issue triage, and collaboration with Product and Engineering.
• Design and maintain the analytics data warehouse, scalable ETL pipelines from PMS, web analytics, and web application sources, and BI capabilities.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 3+ years of professional experience as a Data Scientist and comfort working with large-scale data systems.
• Advanced SQL and Python, including pandas.
• Experience with data orchestration tools such as Airflow, Prefect, or Dagster.
• Proficiency with modern data warehouses such as Snowflake, BigQuery, or Redshift.
• Familiarity with data modeling, data warehousing principles, and BI tools such as ThoughtSpot, Power BI, or Tableau.
• Experience with at least one cloud platform: AWS, GCP, or Azure.
• Strong problem-solving and communication skills, with the ability to manage multiple priorities in a fast-paced startup environment.

Nice to have

• Knowledge of dbt, Kubernetes, Terraform, CI/CD pipelines, and DevOps practices.
• Experience with knowledge worker productivity tools.
• Familiarity with modern data visualization libraries, including D3.js.
• Experience prototyping, building, and testing ML and AI models to validate hypotheses and guide product features.

Culture & Benefits

• Collaborative, inclusive team focused on rigorous thinking and diverse perspectives.
• Equity and comprehensive medical, dental, and vision coverage with covered premiums.
• 401(k), paid time off, wellness, commuter, and FSA stipends.
• Bi-annual in-person company off-sites.
• Opportunity to contribute to product and company growth while working in an early-stage environment.