At a Glance
- Tasks: Lead the People Analytics data ecosystem and develop AI-powered data products.
- Company: Join a leading fintech company revolutionising digital payments.
- Benefits: Flexible work schedule, growth opportunities, and recognition for your impact.
- Other info: Work three days a week in the office and enjoy meaningful challenges.
- Why this job: Make a real difference in data analytics while working with cutting-edge technology.
- Qualifications: Experience in data analysis, strong SQL skills, and a collaborative mindset.
The predicted salary is between 45000 - 55000 £ per year.
Checkout.com provides payment technology that powers digital experiences and enables billions of transactions for global shoppers and businesses. Its platform supports online payments at scale, and the company operates in the fintech sector.
Responsibilities:
- Lead continuous improvement of the People Analytics data ecosystem, including pipeline quality, semantic layers, and shared data products.
- Own the full product development lifecycle for assigned stakeholder groups, from requirements gathering and design to pipeline development, Looker delivery, and enablement.
- Support existing products and deliver new products for Business Partnering and Finance.
- Design, build, and deploy ML models and AI-powered data products.
- Identify high-value use cases from the People Analytics AI roadmap and deliver production-grade solutions.
- Conduct advanced analyses to explain drivers and anticipate future outcomes.
- Partner with the People Analytics Manager and senior stakeholders on complex and strategically important questions.
- Drive data fluency through demos, documentation, training, and self-service tooling.
Requirements:
- Significant experience as a data analyst or analytics engineer in a team with established data engineering practices.
- Strong SQL and hands-on experience with BigQuery or a comparable cloud data warehouse.
- Experience building and maintaining data pipelines with dbt or a comparable transformation tool.
- Experience building dashboards and data products end-to-end for business stakeholders, ideally in Looker.
- Excellent communication skills for translating complex data into clear, actionable insights for non-technical audiences.
- Collaborative, enablement-focused mindset with a focus on self-service.
- Nice to have: Experience with machine learning or statistical modelling in a production context, exposure to AI product development, LLM tooling, or data applications, experience with data quality frameworks, semantic layers, or data observability tooling, prior experience working with HR, people, or workforce data.
Conditions:
- Three days per week in the office.
- The role offers ownership, meaningful challenges, impact recognition, and growth opportunities.
data analyst in People Analytics employer: Enfint
As a leading innovator in AI products for major publishers, our company offers an inspiring work environment where creativity and technology intersect. We prioritise employee growth through continuous learning opportunities and foster a collaborative culture that values diverse perspectives. Located in a vibrant city, we provide competitive salaries, relocation support, and the chance to make a real impact in the media landscape.
StudySmarter Expert Advice🤫
We think this is how you could land data analyst in People Analytics
✨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 Enfint!
✨Show Off Your Projects
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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 Enfint.
✨Apply Directly through Our Website
When you find a suitable opening like data analyst in People Analytics at Enfint, 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 data analyst in People Analytics
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 Enfint, 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 Enfint. 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 Enfint
✨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 Enfint!
✨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.
