At a Glance
- Tasks: Analyse data to support product teams and drive smart business decisions.
- Company: Simply Business, a tech-driven insurance company empowering small businesses.
- Benefits: Permanent position with competitive salary and opportunities for growth.
- Other info: Collaborative environment with a focus on innovation and social impact.
- Why this job: Join an award-winning team and make a real impact on small businesses.
- Qualifications: Experience in data analysis, SQL knowledge, and strong problem-solving skills.
The predicted salary is between 63000 - 77000 £ per year.
Read the overview of this opportunity to understand what skills, including relevant soft skills and software package proficiencies, are required. hackajob is partnering directly with Simply Business to hire for this role.
Who Are We?
We insure small businesses and enable big dreams not just for our customers, but for our people and communities too. With over 1,000,000 active insurance policies, we protect builders, bakers, landlords and more than 1,200 other trades. We're a technology company as well as one that sells insurance. That means we build, we fail, we learn and we improve. Through our global social impact strategy, called 'The Big Dreams Project', we're working to help 10,000 small businesses start or grow by 2030.
What Is the Opportunity?
Here’s what you’ll be doing:
- Data isn’t just numbers to us; it’s the driving force behind how we champion and protect millions of small business owners.
- Joining our award-winning, international data team, you’ll dive headfirst into modern Big Data and analytics technologies to solve real-world problems.
- In this role, you’ll work at the intersection of business strategy and technical innovation.
- You’ll team up with cross-functional developers, data engineers, and data scientists to uncover key customer insights, test bold hypotheses, and build the tools that empower our entire business to make smart, data-driven decisions.
As one of our Senior Product Analysts, you’ll:
- Deliver high quality analysis and recommendations to support the Product teams and help them achieve their objectives.
- Carry out customer journey analysis.
- Measure the impact of multi-channel strategies.
- Uncover and deliver insights through ad-hoc data exploration and visualisation.
- Collaborate with our data engineers to evolve our data sets and data pipelines.
- Build dashboards and self-service query tools and train colleagues to use them.
We’re looking for someone who is:
- An Analyst/Data Scientist or Management Consultant.
- Knowledgeable of SQL.
- Able to prove their aptitude for problem solving and experimentation (A/B tests).
- A collaborator across cross-functional teams.
- Able to prove their aptitude for analysing data.
Senior Product Analyst in Glenrothes employer: Hackajob
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StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Analyst in Glenrothes
✨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 Hackajob!
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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 Hackajob.
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We think you need these skills to ace Senior Product Analyst in Glenrothes
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 Hackajob, 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 Hackajob. 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 Hackajob
✨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 Hackajob!
✨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.
