At a Glance
- Tasks: Analyse data to uncover insights that enhance employee engagement and business performance.
- Company: Join a leading tech company focused on employee satisfaction and productivity.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative team environment with exciting projects and career advancement opportunities.
- Why this job: Make a real impact by solving complex problems with data-driven solutions.
- Qualifications: 3+ years in data science, strong skills in Python, SQL, and R.
The predicted salary is between 50000 - 60000 £ per year.
About the Team
Have you ever wondered what really makes people productive? Or what the triggers are that might make someone choose to leave their job? We're using one of the largest employee engagement datasets in the world to solve mysteries like these. The insights we deliver help our customers run their businesses better, and ensure their employees are more satisfied, motivated and engaged. We're now looking for a Product Data Scientist to join our team and help support our growth. For us, explanation is as important as prediction, and so we use a mixture of classical statistical modelling approaches and ground‑breaking machine learning algorithms to understand how people feel about their experience at work. We use Python for our Science codebase, while the broader tech stack of Peakon centers around JavaScript, with Node.js on the server and React on the frontend. Our data lives in a PostgreSQL database, and we use R for data analysis. We believe in a strong foundation and building things right from the beginning, making our value “Build for tomorrow, today” a guiding principle for the Engineering team.
About the Role
We are looking for someone to join our expanding Commercial Data Science team within Peakon. The perfect candidate will have a background in a quantitative or technical field, experience working with large data sets, and 3+ years experience in enabling data‑driven decision making in a commercial environment. You are focused on results, a self‑starter, and have demonstrated success in using analytics to help your customers maximise the value and strategic impact of their data in solving their business challenges.
Key Responsibilities
- Apply your expertise in statistical analysis, data mining, and the presentation of data to support our customers in maximising the impact of their employee data.
- Lead quantitative analysis projects from start to finish including all aspects of data analysis (e.g. processing, cleaning, verifying the integrity of data used for analysis, statistical analysis, visualisations) and communicating results effectively.
- Act as an expert on specific product features and their implications on data collection to support customer‑facing teams (i.e. Sales, Customer Success, Customer Support).
- Support customer‑facing teams in servicing technical customer data queries that require Data Science support.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities as part of ongoing R&D.
We are looking for a candidate who has a strong desire to work with our customers to solve their complex problems and help develop new solutions, often involving collaboration with different teams across the company. Necessary skills include competence with Python, SQL and R.
About You
The ideal candidate will at minimum have experience in the following areas:
- 3+ years of experience working in a commercial environment with elements of consultancy in their role.
- Responsibility for scoping and delivering bespoke research projects to customers or internal stakeholders within specific timelines.
- Experience communicating complex solutions to audiences with varied technical abilities and understanding.
- In-depth knowledge of statistics (e.g., hypothesis testing, regressions) with an Undergrad, Masters or PhD degree in Computer Science, Math, Physics, Engineering, Statistics or another technical field.
- Strong understanding of SQL.
- Intermediate knowledge of Python or R.
Data Scientist employer: Workday
At Peakon, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through our focus on continuous learning and development, providing opportunities for team members to engage with cutting-edge technologies and methodologies in data science. Located in a vibrant tech hub, we offer a dynamic environment where your contributions directly impact the success of our clients and their employees' engagement, making every day meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, visualisations, and any relevant work you've done. This gives potential employers a taste of what you can bring to the table, especially when it comes to using Python, SQL, and R.
✨Tip Number 3
Prepare for interviews by brushing up on your statistical knowledge and problem-solving skills. Be ready to discuss how you've used data to drive decisions in past roles. Remember, they want to see how you think and approach challenges!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Your Passion for Data:When you're writing your application, let your enthusiasm for data science shine through! Share specific examples of how you've used data to solve problems or drive decisions in your previous roles. We love seeing candidates who are genuinely excited about the impact of their work.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for the Data Scientist role. Highlight relevant experience with Python, SQL, and R, and mention any projects that align with our mission at StudySmarter. This shows us you’ve done your homework and understand what we’re all about!
Be Clear and Concise:Keep your application clear and to the point. Use bullet points where possible to make it easy for us to read through your achievements and skills. Remember, we want to see your qualifications, but we also appreciate a straightforward approach!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our team and culture while you’re at it!
How to prepare for a job interview at Workday
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects involving data analysis. Be ready to discuss specific datasets you've worked with, the challenges you faced, and how you overcame them. This will show your practical experience and understanding of data-driven decision-making.
✨Brush Up on Your Technical Skills
Make sure you're comfortable with Python, SQL, and R, as these are crucial for the role. Practise coding problems or data manipulation tasks that you might encounter in the job. Being able to demonstrate your technical prowess during the interview can set you apart from other candidates.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve hypothetical problems using data. Think about how you would approach a project from start to finish, including data cleaning, analysis, and visualisation. This will help you articulate your thought process and problem-solving skills effectively.
✨Communicate Clearly and Confidently
Since you'll be working with various teams, it's essential to convey complex ideas simply. Practise explaining your past work to someone without a technical background. This will demonstrate your ability to communicate effectively with customer-facing teams and stakeholders.
