How does swipeandhired work?

You set your target roles, salary floor and locations once. swipeandhired scores matching postings against your profile, drafts tailored application materials with AI, and either lets you swipe to apply, one tap at a time, or runs fully on autopilot. Every application is tracked in your dashboard.

Which ATS platforms does swipeandhired support?

All of them. swipeandhired applies on every applicant tracking system (ATS) employers use, including Workday, SmartRecruiters, Greenhouse, iCIMS, Lever, Ashby, Taleo, SuccessFactors, Oracle Cloud and Jobvite, and on a company's own careers page when it uses none of them. You can also bring any posting yourself by link or pasted text.

Can I cancel my subscription?

Anytime, in one click from the billing portal in Settings. Your plan stays active until the end of the current billing period. No retention calls, no dark patterns.

Is my data used for training AI models?

No. Your resume and application data are processed only to run the service for you, matching, drafting, and submitting applications. We never sell your data. If you bring your own AI provider key, requests go directly to your provider under their terms.

Product Analyst at This is Global, Holborn - London

Product Analyst at This is Global in Holborn - London. Full-time. Est. up to $80k. Apply with swipeandhired.

Accepting applications until:
27 November 2026

Job Description
Job Title: Product Analyst

Your new rol e
We’re looking for a commercially minded Product Analyst with experience in product analytics, data analysis, or a similar insight-led role, ideally gained in a fast-paced, data-driven business.

As a Product Analyst in Global’s DAX Product team, you’ll help squads make better product decisions through data discovery, insight generation, requirements gathering, and structured analytical problem-solving. You’ll report to the Product Lead and work closely with the Senior Product Owner in the DAX Data Engineering squad, alongside other Product Owners, Engineers, Operations, and commercial stakeholders across DAX.

This is not a purely reporting-led role. You’ll turn ambiguous questions into clear analysis, investigate trends and anomalies in product, operational, and commercial data, and provide evidence-based recommendations that inform product discovery, prioritisation, strategy, and OKRs.

It’s a great opportunity for someone who is naturally curious, commercially aware, and excited by using data to influence product direction across a complex and evolving ad-tech landscape.

Key Responsibilities

Product-led data discovery and insight generation (50%)
You will work across DAX squads to investigate product, operational, and commercial data in order to uncover insights, identify trends, and support decision-making. You’ll help teams answer key questions through structured analysis, benchmarking, and exploratory data work, including investigating anomalies and patterns in DAX data such as spotting trends, delivery behaviours, or product performance shifts.

Analytical solution design (25%)
You will partner with Product Owners, Engineers, and Stakeholders to understand business needs to then build dashboards or analytical outputs that support product discovery, trouble-shooting, prioritisation, and ongoing performance monitoring.

Supporting product strategy, OKRs, and continuous improvement (25%)
You will contribute to OKR setting and product planning by providing robust data, benchmarks, and performance insights. You’ll support squads in measuring success, understanding opportunities, and improving how they use data in decision-making. You’ll also help improve analytical ways of working, data quality awareness, and reporting consistency across the DAX product organisation.

What You’ll Love About This Rol e

Think Big: Help shape how data informs product thinking across DAX, bringing a strategic mindset to product discovery and decision-making.

Own It: Take responsibility for turning ambiguous questions into clear analysis, actionable insight, and meaningful recommendations.

Keep it Simple: Use data to cut through complexity, focusing on the metrics and insights that matter most.

Better Together: Collaborate across squads, disciplines, and stakeholders to help build a stronger, more insight-led product organisation.

What Success Looks Like
In your first few months, you’ll have:

Built a strong understanding of the DAX product landscape, including how different squads operate and where data can most effectively support product discovery and decision-making

Developed a good working relationships across the DAX technology teams (e.g. engineers, product owners, design, etc.) and key stakeholders outside technology

Become familiar with the main datasets, dashboards, workflows, and systems used across the DAX environment

Supported product squads by investigating questions, identifying data trends or anomalies, and turning findings into clear recommendations / actionable insights

Contributed to requirements gathering for analytical work and helped shape dashboards, reporting, or exploratory analysis that supports squad priorities

Added value to OKR discussions and benchmarking exercises through thoughtful analysis and evidence-based input

What You’ll Need

3+ years experience in a Product Analyst, Data Analyst, or similar analytical role

Experience working closely with product, engineering, or delivery teams to support discovery, prioritisation, and product decision-making

Demonstrated ability to take work from problem definition and requirements gathering through to analysis, insight, and presentation

Strong experience working with large and complex datasets in a commercial environment

Strong SQL skills and confidence querying, validating, and exploring data independently

•. Experience with dash boarding and visualisation tools such as Tableau, Power BI, or similar

Experience building clear, useful dashboards and reporting to support business and product stakeholders

A strong analytical mindset, with the curiosity to investigate trends, spot anomalies, and ask the right questions

The ability to translate complex findings into simple, compelling narratives and recommendations for non-technical audiences

Excellent stakeholder management and collaboration skills, with the ability to work effectively across multiple squads and functions

Strong attention to detail and a structured approach to problem solving