At a Glance
- Tasks: Lead the evolution of our data platform for advanced analytics and AI.
- Company: Join a warm and supportive company with a global reach.
- Benefits: Competitive salary, hybrid working, birthday holiday, and comprehensive benefits.
- Other info: Collaborative environment with opportunities for growth and innovation.
- Why this job: Make a real impact by bridging business and technology in data management.
- Qualifications: Experience in product management and a degree in a related field.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Data Product Manager to define and evolve our data platform as a strategic product, enabling advanced analytics and AI readiness. This role bridges business and technology to ensure scalable, secure, and commercially valuable data capabilities.
Key responsibilities
- Position the data platform as a scalable, reusable internal product.
- Identify and address capability gaps across analytics, AI, and machine learning use cases.
- Own and prioritise the product backlog across data ingestion, storage, quality, and governance.
- Translate strategic objectives into clear deliverables, metrics, and outcomes.
- Partner with Data Engineering and ML teams to deliver in an agile environment.
- Establish standards for data quality, governance, and trust.
- Ensure platform readiness for advanced analytics, MLOps, and AI deployment.
- Collaborate with commercial teams to align platform capabilities with revenue opportunities.
- Communicate progress, risks, and complex concepts clearly to stakeholders.
About you
- Significant experience in product management within data, analytics, or AI environments.
- Strong understanding of modern data platforms, cloud technologies, and data lifecycle management.
- Ability to collaborate effectively with technical and non‑technical stakeholders.
- Commercial mindset with a focus on delivering measurable business value.
- Degree in Computer Science, Engineering, Information Systems, or a related field.
Benefits
- Competitive salary and incentive scheme.
- Warm, supportive, and open company culture.
- Opportunity to thrive in a global environment.
- Hybrid working: 3 days in the office.
- Birthday holiday and option to purchase additional annual leave.
- Comprehensive Benefits Package: Private Pension, Private Medical Insurance, Life Assurance and more.
Location: 566 Chiswick High Rd, London W4 5YE.
Data Product Manager employer: International SOS
As a Data Product Manager at our company, you will thrive in a warm and supportive culture that values collaboration and innovation. With a competitive salary, comprehensive benefits package, and the flexibility of hybrid working, we empower our employees to grow and excel in a global environment. Join us in London, where your contributions will directly impact our advanced analytics and AI readiness, making this an exciting and rewarding opportunity.
StudySmarter Expert Advice🤫
We think this is how you could land Data Product Manager
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like International SOS.
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We think you need these skills to ace Data Product Manager
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at International SOS, 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 International SOS. 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 International SOS
✨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!
✨Showcase Your Projects
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 International SOS!
✨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.
