About the Role

We're looking for an Analytics Engineer to own the accuracy, reliability, and scalability of our financial data and reporting, across all of our brands.

This role sits at the intersection of finance, commercial, data, operations and engineering. You'll make sure that all of our financial models, across all of our markets, are standardised, reliable and well documented, for both internal and external reporting.

You'll work closely with the finance and commercial teams for requirements, and the engineering and operations teams globally to shape the data we collect, to produce best in class financial data models. The expectation is full end-to-end ownership: implementation, governance, data quality monitoring, and documentation. We're scaling across multiple markets, and the rigour of our financial tracking data is directly tied to the quality of decision-making within each markets, and the business’s ability to correctly allocate capital to each market.

What You'll Own

Revenue Models

• Maintain and improve the accuracy and reliability of our core orders, revenue & refunds models.
• Configure and manage integrations with financial reporting tools, eg. Netsuite.
• Standardise reporting across each region (UK, EU, AU, JP, CA).
• Partner with engineering and operations, to manage changes across products and processes, reducing downstream reporting impacts.

SEC Reporting Models

• Work with the US Hims & Hers financial team, to provide accurate, reliable and well documented data for SEC reporting.
• Build automated checks for data reliability, and monitor drift of reporting figures.
• Maintain a deep understanding of upstream source data to understand change impacts to reporting figures.

Payback Models

• Accurately model our product COGs and services costs, with our revenue data to build payback models to help inform capital allocation decisions
• Work closely with the finance, commercial and operations teams to maintain our product COGs data
• Work with the marketing teams to accurately track and attribute our marketing spend data (google, facebook, tiktok, etc)

Data quality and validation

• Monitor and validate data accuracy across financial source data
• Build automated checks for missing or duplicated data, schema drift, and anomalies
• Investigate discrepancies between source data and reported figures.
• Maintain end to end documentation of reporting models

About You

• 4-6 years in an analytics engineering, financial or commercial analytics
• Experience building / maintaining production data models
• Strong SQL skills, ideally in BigQuery, for data modelling and validation
• Detail orientated, able to self-validate assumptions and potential data gaps
• Strong sense of ownership
• Familiarity with dbt or similar transformation tools
• Familiarity with financial concepts, eg. Revenue, CAC, Payback, LTV
• Strong documentation habits — you fix things and write it down

Nice to have

• Experience with providing data for public market reporting
• Experience with financial data, Stripe, Zip, etc
• Exposure to ERP tools, eg Netsuite
• Experience with BI tools, eg Sigma