At a Glance
- Tasks: Lead the vision and delivery of a cutting-edge analytics platform transforming sensor data into insights.
- Company: Join a forward-thinking company at the forefront of intelligent sensing and analytics.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to make a real-world impact in high-tech sectors.
- Why this job: Shape the future of analytics while collaborating with diverse teams and innovative technologies.
- Qualifications: Experience in product ownership and a strong understanding of analytics and sensor data.
Product Owner – Analytics
Shape the future of intelligent sensing and advanced analytics.
We're looking for an experienced Product Owner to lead the vision and delivery of a sophisticated analytics platform that transforms complex sensor data into meaningful operational insight.
Working at the intersection of product, engineering and data science, you'll define priorities, drive measurable improvements, and ensure analytics capabilities continue to evolve in line with customer needs and technical innovation.
Key Responsibilities
- Define and own the product roadmap for a complex analytics platform, balancing short and long-term priorities.
- Lead the product backlog, ensuring requirements are clearly defined and ready for delivery.
- Establish measurable performance targets for analytics, tracking, classification and decision-support capabilities.
- Work closely with data scientists to translate machine learning and analytical models into production-ready features.
- Collaborate with software engineers, technical specialists and customers to refine requirements and validate delivered functionality.
- Monitor product performance using data and metrics, driving continuous improvement through evidence-based decision making.
- Support agile delivery by prioritising work, accepting completed features and maintaining alignment across multidisciplinary teams.
- Spend time with customers and operational users to understand workflows and ensure the product delivers real-world value.
Requirements
- Experience as a Product Owner or Product Manager delivering complex software or analytics-based products.
- Strong understanding of sensor data processing, tracking, data fusion or advanced analytics.
- A data-driven approach with experience defining KPIs, measuring performance and using evidence to prioritise product decisions.
- Experience working alongside data science and engineering teams to deliver technical products.
- Proven ability to translate customer and operational requirements into clear, prioritised user stories and product backlogs.
- Experience using Azure Dev Ops or similar agile work management tools.
- Excellent communication and stakeholder management skills, with the ability to work across technical and non-technical teams.
Desirable
- Experience within defence, aerospace, security, autonomous systems or other high-technology engineering sectors.
- Knowledge of radar, RF, electro-optical or other sensor technologies.
- Background in engineering, physics, mathematics, data science or a related technical discipline.
- Experience delivering AI, machine learning or analytics-driven products.
- Familiarity with decision-support systems or operational software platforms.
Please note: This is a hybrid role based around regular attendance at the Reading office, with occasional travel to operational sites
Product Owner in Reading employer: Technify Talent Limited
Technify Talent Limited is an exceptional employer, offering a dynamic work environment in Spencers Wood, UK, where innovation meets collaboration. Employees benefit from comprehensive training and development opportunities, fostering both personal and professional growth while working on cutting-edge technology in the drone and sensor systems sector. The company promotes a supportive culture that values teamwork and encourages a customer-focused approach, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Product Owner in Reading
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Technify Talent Limited!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Product Owner at Technify Talent Limited.
✨Leverage Professional Networks
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 Technify Talent Limited.
✨Apply Directly through Our Website
When you find a suitable opening like Product Owner at Technify Talent Limited, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Product Owner in Reading
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 Technify Talent Limited, 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 Technify Talent Limited. 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 Technify Talent Limited
✨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 Technify Talent Limited!
✨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.
