Senior TA Analytics Lead - Predictive Insights & AI Tools

Uber; United States; On-site; USD 131,000 - 145,000; Full time

Benefits offered by this job

Bonuses

Equity

Benefits

Job summary

Uber is seeking a TA Analytics professional to transform recruiting into a proactive, data-driven function. You will build predictive models with Python or R, evaluate AI tools for ROI and bias, and define metrics like Quality of Hire.

You will partner with data engineers to optimize pipelines and drive prescriptive insights through dashboards. The role emphasizes strategic analytics, cross-functional collaboration, and ownership from requirements to deployment in a fast-paced environment.

Qualifications

• BS/MS in Engineering, CS, Math, Economics, Statistics, or similar quantitative field.
• 3+ years in data analysis, data science, analytics engineering, or similar.
• Proficiency in Python or R for modeling and data manipulation.
• Strong SQL skills with MySQL, BigQuery, and modern data stores.

Responsibilities

• Build predictive models forecasting pipeline health, conversion, time-to-fill, and quality.
• Evaluate AI tools, ROI, efficacy, and bias in recruiting tech stack.
• Define metrics like QoH and skills-based hiring efficacy.
• Model data and improve data pipelines with data warehouse engineers.
• Lead visualization strategy and create dashboards for prescriptive insights.
• Support ad-hoc analytics requests within TA and People org.

Skills

Python

R

Advanced SQL

Data manipulation

Statistical modeling

Analytics storytelling

Education

BS/MS in Engineering or CS or Math

Tools

MySQL

BigQuery

Looker

Power BI

Tableau

Dataform

dbt

GitHub

Job description

Uber is seeking a TA Analytics professional to transform recruiting into a proactive, data-driven function. You will build predictive models with Python or R, evaluate AI tools for ROI and bias, and define metrics like Quality of Hire.

You will partner with data engineers to optimize pipelines and drive prescriptive insights through dashboards. The role emphasizes strategic analytics, cross-functional collaboration, and ownership from requirements to deployment in a fast-paced environment.