Senior Data Scientist, People and Talent

Airwallex1 weeks ago

Location

US - San Francisco

Type

Full Time

Salary

USD 160,000 – 250,000

Level

Senior

Role

Data Engineer

Posted

Jul 2, 2026

Full TimeSenior

The role

Summary

As Senior Data Scientist for People and Talent at Airwallex, you'll own the HR and recruiting data domain, building scalable analytics foundations that power people decisions across a 2,200+ person, 26-country organization. You'll combine hands-on data engineering with product thinking to design data models, pipelines, and self-serve analytics tools while managing data governance and enabling AI-powered insights for the People & Talent, Finance, and Revenue Strategy functions. This role requires 5+ years of experience in data science/analytics with advanced expertise in SQL, Python, cloud platforms like Databricks, and demonstrated success translating ambiguous business challenges into production-quality analytics solutions.

What you'll do

Own People & Talent Data Domain: Manage all P&T data assets including robust data models, ETL pipelines, comprehensive documentation, and governance protocols across HR and recruiting systems including BambooHR, Ashby, and HRIS/ATS platforms.

Design and Deploy Analytics Infrastructure: Build and maintain scalable dashboards, reports, and self-serve analytics platforms supporting stakeholders in People & Talent, Finance, Revenue Strategy, and Engineering using tools like Hex, Databricks, and dbt.

Manage Analytics Roadmap and Prioritization: Partner with cross-functional teams to prioritize data requests, develop and execute the P&T analytics roadmap, and drive continuous improvements in automation, data quality, and end-user access workflows.

Subject Matter Expert and Data Governance Lead: Act as the authoritative subject matter expert on people data, supporting metric definition, troubleshooting complex data issues, providing user guidance, and enforcing strict governance and privacy standards for sensitive HR data.

Enable AI-Powered Analytics Capabilities: Identify and implement AI-enabled and self-serve analytics use cases, including LLM-powered data access solutions, to enhance the P&T analytics ecosystem and support global organizational growth.

Translate Business Requirements into Analytics Solutions: Work with business leaders to transform ambiguous challenges into well-defined analytics projects using structured problem-solving methodologies and clear communication of insights to both technical and non-technical audiences.

What we look for

Technical

SQL MasteryAdvanced hands-on proficiency in SQL for complex data transformations, large dataset manipulation, and building robust, production-grade data queries.

Python/R ProgrammingStrong programming skills in Python and/or R for data analysis, statistical modeling, and building scalable analytics solutions.

Cloud Data PlatformsProduction experience with cloud data platforms such as Databricks, with practical knowledge of Delta Lake, data warehousing architectures, and distributed computing.

Data Transformation FrameworksHands-on experience with dbt or similar transformation frameworks for building modular, tested, and version-controlled data pipelines.

Analytics and Visualization ToolsProficiency with notebook-based analytics platforms like Hex, including strong documentation practices and visualization best practices.

Statistical Methods and ExperimentationExpertise in causal inference, A/B testing design, experimentation frameworks, and forecasting methodologies to analyze and explain metric changes.

HR/Recruiting SystemsHands-on experience with HR and recruiting data systems (BambooHR, Ashby, HRIS/ATS platforms), including understanding of data quirks, unique identifiers, and common update patterns.

Education

Advanced Degree RequiredMS or PhD in Statistics, Computer Science, Engineering, Economics, or a closely related quantitative field.

Technical FoundationStrong mathematical and statistical background with demonstrated coursework or projects in data analysis, machine learning, or related disciplines.

Experience

5+ Years Data Science/Analytics ExperienceProven experience in data science, analytics, or related quantitative fields with demonstrated end-to-end ownership of data models, pipelines, and dashboards in production environments at scale.

Data Modeling and Pipeline OwnershipTrack record of designing and implementing production data solutions, managing complex data pipelines, and ensuring data quality and governance at enterprise scale.

Cross-functional Stakeholder ManagementExperience working across diverse teams (product, finance, engineering, operations) to translate business requirements into technical solutions and influence data strategy.

People/HR Analytics Domain ExperienceExposure to high-growth technology or fintech environments with demonstrated success in People & Talent analytics, especially where it intersects with Finance, Revenue Strategy, or GTM initiatives.

Skills

Required skills

SQLAdvanced SQL for complex queries, data transformations, and working with large, complex datasets in production environments.

PythonStrong Python programming for data analysis, statistical modeling, and building analytics solutions at scale.

Databricks and Cloud Data PlatformsProduction experience with Databricks, Delta Lake, and cloud data warehouse architectures.

dbt (Data Build Tool)Experience building modular, tested data transformation pipelines with dbt or similar frameworks.

Statistical AnalysisExpertise in causal inference, experimentation, forecasting, and statistical methods for explaining metric changes.

Data Governance and PrivacyUnderstanding and application of rigorous data governance, privacy standards, and user access controls for sensitive data.

HR/Recruiting Data SystemsFamiliarity with BambooHR, Ashby, HRIS/ATS platforms, and common HR data structures and patterns.

Nice to have

R ProgrammingExperience with R for statistical analysis and advanced analytics work complements Python skills.

Hex or Notebook-Based AnalyticsProficiency with Hex, Jupyter, or similar platforms for collaborative analytics and documentation.

AI-Powered AnalyticsExperience building AI-powered analytics solutions, self-serve tools, or LLM-powered data access platforms.

Fintech or High-Growth Tech BackgroundExperience in fast-growing financial technology or SaaS environments where People & Talent analytics supports business scaling.

People Analytics SpecializationDemonstrated expertise in HR metrics, workforce planning, talent analytics, or recruiting analytics.

Exceptional Communication SkillsAbility to explain complex technical concepts to non-technical stakeholders and build strong cross-functional partnerships.

Compensation & benefits

Salary

USD 160,000 – 250,000 (annual)

Stock options

Available

Benefits

Global Career Growth

Opportunity to grow your data science and analytics career at a 2,200+ person organization spanning 26 offices globally, with exposure to high-impact business decisions at scale.

Cutting-Edge Technology Stack

Work with modern cloud data platforms, distributed computing, and AI-powered analytics tools used by leading fintech companies.

High-Impact Work

Partner directly with executive leadership and cross-functional teams on mission-critical people decisions that shape organizational strategy and global expansion.

Mentorship and Learning

Learn from experienced data science and engineering teams at a unicorn-valued fintech company backed by T. Rowe Price, Visa, Mastercard, and Sequoia Capital.

Domain Expertise Development

Deep specialization in People & Talent analytics within a high-growth financial services environment, positioning you as a subject matter expert in HR data strategy.

Ownership and Autonomy

Own an entire data domain end-to-end, with full responsibility for data modeling, governance, and analytics strategy for the People & Talent function.

Interview process

1
Initial Screening and Qualification Call — Hiring manager or recruiter reviews your background against core requirements (5+ years analytics experience, advanced degree, SQL/Python proficiency) and discusses your experience with data modeling, pipelines, and governance.
2
Technical Skills Assessment — Evaluate hands-on technical capabilities through a portfolio review or brief technical screening covering SQL query optimization, Python data analysis, and understanding of cloud data platforms like Databricks and dbt workflows.
3
Case Study or Data Analysis Project — Present a real-world or simulated analytics challenge where you demonstrate your ability to translate business requirements into data solutions, including data modeling decisions, analysis approach, and stakeholder communication.
4
Cross-Functional Stakeholder Round — Meet with People & Talent leaders, Finance partners, and potentially Engineering stakeholders to discuss collaboration style, understanding of HR analytics challenges, and ability to manage competing priorities across departments.
5
Final Conversation with Hiring Leader — Discussion with the senior leader overseeing this role to align on long-term vision for the P&T data domain, your approach to building scalable analytics infrastructure, and cultural fit within Airwallex's builder-oriented, high-ownership environment.