At a Glance
- Tasks: Map HR processes, assess data quality, and document standards in an AI programme.
- Company: Join a forward-thinking company transforming HR with AI technology.
- Benefits: Hybrid work model, ownership of projects, and exposure to cutting-edge AI applications.
- Other info: Opportunity for career growth across various HR technology functions.
- Why this job: Be part of a team shaping the future of HR through innovative AI solutions.
- Qualifications: Two years in process or data analysis, with hands-on experience in real organisations.
The predicted salary is between 45000 - 55000 £ per year.
HR Technology and Change | London, hybrid
This is a process and data role.
The work sits inside an AI programme, and you will end up understanding a lot about how AI operates If you are the person who actually maps the process, finds the seventeen exceptions nobody documented, and works out which of them matter, keep reading.
The role
- Our client is rebuilding how its HR function works, moving from people navigating systems to asking questions in plain language and getting reliable answers back.
- You will map HR processes end to end, capturing decision points, roles involved and exception handling.
- You will run data quality assessments, work out root causes, and get issues fixed at source rather than patched afterwards.
- You will document standards and definitions, maintain the process library, and flag where a process is too vague or inconsistent to automate safely.
- The function is being built now, and you will help write the playbook, not inherit one.
- What we need you to have done
- Process mapping, hands on. Non-negotiable. Real processes, in a real organisation, to a proper level of detail, working directly with the people who own them.
- Minimum two years in a process analyst, business analyst, data analyst or similar role.
- Experience working with sensitive information and stakeholders across a business.
HR is ideal but not required.
Finance, risk, legal, operations or any confidential-data function counts.
- Comfort with data: spotting quality problems, tracing where they come from, tracking them through to a fix.
- Helpful, not essential
- HR or HR systems exposure (Workday, Service Now, Success Factors or similar)
- Hands-on experience with AI tooling, automation or agents
- Process improvement methodologies (Lean, Six Sigma or similar)
- What you get
- Real ownership of a domain that matters.
- Genuine exposure to how AI is being deployed responsibly at enterprise scale, from the inside.
- A team that expects you to move around it over time, across HR technology, delivery and reporting, rather than stay in one lane.
- #J-18808-Ljbffr
Process and Data Analyst employer: ARC IT Recruitment
As a leading Tier 1 main contractor based in Cambridge, we pride ourselves on fostering a dynamic work culture that prioritises employee growth and development. Our commitment to delivering high-value commercial construction projects not only ensures job satisfaction but also offers competitive salaries and comprehensive packages, making us an excellent employer for those seeking meaningful and rewarding careers in the construction industry.
StudySmarter Expert Advice🤫
We think this is how you could land Process and Data Analyst
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We think you need these skills to ace Process and Data Analyst
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 ARC IT Recruitment, 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 ARC IT Recruitment. 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 ARC IT Recruitment
✨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 ARC IT Recruitment!
✨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.
