Senior Product Analyst
About the Business
At ICIS, our mission is to optimize the world’s resources. We help companies make strategic, sustainable decisions by bringing transparency to markets across the world. We create a comprehensive view of commodities markets, providing companies with the data and intelligence to successfully navigate across global value chains every day. Our customers benefit from instant access to price assessments, reports and forecasts, a dedicated news channel and supply and demand data. You can learn more about ICIS at the link below.
https://www.icis.com/explore
About our Team
The product team play a pivotal role in growing and evolving ICIS’ suite of data, insight and analytics services. The team is globally located, and drives alignment across the business, interacting regularly with technology, design, sales, marketing, content, customer success
About the Role
Our aim is to give companies in global commodities markets a comparative advantage. Delivering trusted pricing data, high value news, analysis, and independent consulting, enabling our customers to make better-informed trading and planning decisions.
As a Senior Product Analyst at ICIS, you’ll lead analytics within the Product Team. Our aim is understanding customer engagement, improving product performance, and leading in steering business and strategic decisions. Product Analytics is essential to pioneer new ways to gain insight into customer behaviour and driving product development.

Responsibilities

• Leading on analyses to understand the drivers behind customer behaviour and communicate to the wider team to inform on product strategy.
• Taking charge of owning and governing out usage data across all products and services. Consult as a subject matter expert, providing expertise for various projects and queries.
• Driving data literacy across the business by providing training, directing self-serve analyses, and assisting with queries.
• Participating in the design and research discussions for new releases. Provide statistical reports when needed for data driven decision making.
• Developing data engineering solutions to pre process data and enhance analyses by mapping to external and internal sources.

Requirements

• Experience in SQL, Python/R, advanced data preparation and visualisation, and statistical analysis.
• Experience with building out visualisations and dashboards in Power BI/Tableau and Adobe Analytics.
• Demonstrate problem-solving skills and the ability to generate actionable insights from data.
• Manage to effectively communicate analyses and hypotheses to diverse groups and levels within the organisation.

Learn more about the LexisNexis Risk team and how we work
here

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At LexisNexis Risk Solutions, having diverse employees with different perspectives is key to creating innovative new products for our global customers. We have 30 diversity employee networks globally and prioritize inclusive leadership and equitable processes as part of our culture. Our aim is for every employee to be the best version of themselves. We would actively welcome applications from candidates of diverse backgrounds and underrepresented groups.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form:
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• Leading on analyses to understand the drivers behind customer behaviour and communicate to the wider team to inform on product strategy.
• Taking charge of owning and governing out usage data across all products and services. Consult as a subject matter expert, providing expertise for various projects and queries.
• Driving data literacy across the business by providing training, directing self-serve analyses, and assisting with queries.
• Participating in the design and research discussions for new releases. Provide statistical reports when needed for data driven decision making.
• Developing data engineering solutions to pre process data and enhance analyses by mapping to external and internal sources