At a Glance
- Tasks: Create bespoke dashboards and data products to support community partners.
- Company: Join a dynamic team at QCAP, focused on impactful data solutions.
- Benefits: Gain valuable experience, network across the University, and enhance your skills.
- Other info: Opportunity to work with cutting-edge data visualisation tools and technologies.
- Why this job: Make a real difference by leveraging data for community action.
- Qualifications: Degree in Data Science or related field, plus 3 years of relevant experience.
The predicted salary is between 34650 - 42350 £ per year.
About the job: This post plays a key role in QCAP's Data for Action Pillar providing data products expertise and support in developing bespoke dashboards and other novel products to our community partners. Using expertise to support QCAP staff and community partners the role holder will be a point of contact for all data related issues and as such will be required to network more broadly across the University and with key external stakeholders. About the person: Essential Criteria: Hold at least a 2:1 degree (or equivalent) in Data Science, Computer Science or a related field OR substantial relevant experience in similar role(s) Significant relevant experience - minimum of 3 years' (e.g. as a Data Technician/ Data Analyst or in a closely related role). Demonstrable knowledge and experience in the creation of and interrogation of interactive data visualisations and dashboards. Demonstrable experience and proficiency in Python and/or R. Demonstrable experience of the ability to write and maintain clean, efficient, and well-documented code for data analysis and statistical tasks. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our website. TPBN1_NI
QCAP Data Manager in Belfast employer: Queens University
As a Principal Engineer at Momentum One Zero, you will be part of a dynamic and innovative team dedicated to pushing the boundaries of ML/AI engineering in exciting fields like digital health and agri-food. Our collaborative work culture fosters creativity and professional growth, offering ample opportunities for skill development and career advancement in a supportive environment. Located in a vibrant area, we provide a unique chance to engage with industry partners while contributing to impactful projects that make a real difference.
StudySmarter Expert Advice🤫
We think this is how you could land QCAP Data Manager in Belfast
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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 Queens University!
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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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How to prepare for a job interview at Queens University
✨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
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✨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.
