At a Glance
- Tasks: Lead the Foundry Platform backlog and shape the vision for data and AI projects.
- Company: Join LexisNexis Risk Solutions, a leader in data and analytics.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Be part of a dynamic team focused on enhancing data quality and governance.
- Why this job: Make a real impact by driving innovation in data and AI solutions.
- Qualifications: Experience in product ownership and a strong understanding of data and APIs.
The predicted salary is between 60000 - 80000 £ per year.
Lexis Nexis Risk Solutions is looking for a Platform Product Owner to lead the Foundry Platform backlog, shaping the vision and delivery across data, APIs and AI-enabled assets.
You will work with engineering, data teams and business stakeholders to translate requirements into scalable platform capabilities.
The role emphasizes prioritization, governance and reliability, ensuring adoption and data quality improvements across the organisation.
Senior Platform Product Owner - Data & AI Foundry employer: LexisNexis Risk Solutions
At ICIS, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and accountability. Our commitment to employee well-being is reflected in our generous benefits package, extensive learning opportunities, and a supportive environment that encourages personal and professional growth. Join us in our mission to optimize the world's resources while enjoying a fulfilling career in a globally distributed team that values your insights and contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Platform Product Owner - Data & AI Foundry
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We think you need these skills to ace Senior Platform Product Owner - Data & AI Foundry
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at LexisNexis Risk Solutions, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at LexisNexis Risk Solutions. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at LexisNexis Risk Solutions!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
