At a Glance
- Tasks: Transform business needs into data-driven solutions and conduct impactful analyses.
- Company: Join a forward-thinking analytics firm with a focus on collaboration and innovation.
- Benefits: Enjoy private healthcare, generous leave, and a strong pension scheme.
- Other info: Embrace a culture of equality and community involvement with excellent career growth.
- Why this job: Make a real difference using advanced analytics across diverse sectors.
- Qualifications: Degree in data science or related field; experience in analytics and model building.
The predicted salary is between 50000 - 70000 £ per year.
Responsibilities
- Work with clients to translate business needs into analytical approaches and solutions.
- Conduct analysis for evidence‑based decision making, including model design, build, testing, and hand‑over.
- Use agile best practices and collaborate cross‑functionally with product, design and other experts.
- Lead whiteboard sessions and provide technical problem‑solving support to clients and internal teams.
- Work on internal projects and client projects across multiple sectors, using data‑centric analytics and advanced modelling techniques.
- Communicate findings and recommendations to technical and non‑technical audiences.
- Utilize a range of tools (Python, SQL, Excel, data visualisation, big‑data, cloud platforms) as required.
Qualifications
- A degree, master’s or PhD in data science, mathematics, operational research, physics, or statistics.
- Experience conducting analysis and building models for evidence‑based decision making.
- Experience translating business needs into analytical solutions and communicating to stakeholders.
- Experience across the full analytics and modelling lifecycle: problem formulation, exploratory data analysis, model design, build, testing, and hand‑over.
- Proficiency with Python, SQL, Excel and data visualisation tools.
- Experience with data engineering, big‑data, cloud platforms or dashboard development preferred.
- Strong stakeholder management, project management and communication skills.
- Experience in the software or product development lifecycle for analytical solutions is a plus.
- Experience in client presentations and developing data and behavioural science propositions is a plus.
- UK work eligibility and security clearance: UK roles may require baseline personnel security standard and, for some roles, higher level of national security vetting including at least 5 years of continuous residency in the UK.
Benefits
- Private healthcare for you and your family.
- 25 days annual leave (plus a bonus half day on Christmas Eve) and the opportunity to purchase additional days.
- Generous pension scheme.
- Opportunities to get involved with community and charity initiatives.
- Annual performance‑based bonus.
- Share ownership and tax‑efficient benefits (cycle‑to‑work, give‑as‑you‑earn).
We are committed to advancing equality. We recruit, retain, reward and develop our people based solely on their abilities and contributions and without reference to age, background, disability, genetic information, parental or family status, religion or belief, race, ethnicity, nationality, sex, sexual orientation, gender identity, or political belief. We welcome applications from under‑represented groups. Adjustments or accommodations can be provided to support the recruitment process. Please contact recruitmentenquiries@paconsulting.com for more information.
Advanced Data Analytics in Belfast employer: Spalding Consulting
At our company, we pride ourselves on being an exceptional employer that fosters a collaborative and inclusive work culture. With a strong focus on employee growth, we offer extensive training opportunities and the chance to work on diverse projects across multiple sectors, all while enjoying generous benefits such as private healthcare, a robust pension scheme, and a commitment to community initiatives. Located in the UK, we are dedicated to advancing equality and ensuring that every team member's contributions are recognised and valued.
StudySmarter Expert Advice🤫
We think this is how you could land Advanced Data Analytics in Belfast
✨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 Spalding Consulting!
✨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 Advanced Data Analytics at Spalding Consulting.
✨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 Spalding Consulting.
✨Apply Directly through Our Website
When you find a suitable opening like Advanced Data Analytics at Spalding Consulting, 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 Advanced Data Analytics in Belfast
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 Spalding Consulting, 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 Spalding Consulting. 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 Spalding Consulting
✨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 Spalding Consulting!
✨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.
