At a Glance
- Tasks: Analyse complex datasets and build predictive models to drive data-driven decisions.
- Company: Join Domino's Pizza UK & Ireland, a leader in the food industry.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative team environment with continuous learning opportunities.
- Why this job: Make an impact by optimising processes and enhancing customer experiences.
- Qualifications: Degree in a quantitative field; programming skills in Python or R preferred.
The predicted salary is between 30000 - 40000 £ per year.
hackajob is collaborating with Dominos Pizza UK & Ireland to connect them with exceptional professionals for this role.
Job Purpose
To support the organisation’s data-driven decision making by analysing complex datasets, building predictive models, and generating actionable insights. Work closely with senior data scientists and business stakeholders to ensure the insights enable decisions that optimise processes, improve customer experiences, and contribute to commercial growth.
Key Responsibilities/Job Tasks
- Assist in collecting, cleaning, and preparing data from various sources for analysis and modelling.
- Work on well-defined data science problems with clear success criteria.
- Build, test, and deploy basic predictive models under the guidance of senior team members.
- Support the development of dashboards and automated reports for business stakeholders.
- Contribute to A/B testing and experimentation to improve product features and customer journeys.
- Collaborate with cross-functional teams (e.g., analytics, marketing, product, operations) to understand requirements and deliver data solutions.
- Present findings and insights in a clear, concise manner to both technical and non-technical audiences.
- Continuously learn new tools, techniques, and best practices in data science and analytics.
Skills & Job Requirements
The Junior Data Scientist supports the development and implementation of analytical solutions. While not accountable for setting strategy, the role provides valuable input through data exploration, model building, and insight generation that inform strategic decisions.
Able to work with stakeholders to identify business problems and help build solutions using data science and advanced analytics. Can identify value metrics that will drive adoption.
Regularly tackles data-related challenges such as missing values, outliers, and inconsistent formats. Uses logical reasoning and statistical techniques to resolve issues, often seeking guidance from senior colleagues. Applies creative thinking to experiment with different modelling approaches and improve solution accuracy.
Makes decisions within defined procedures and guidelines, such as selecting appropriate data cleaning methods or choosing basic modelling techniques. Escalates complex or high-impact decisions to senior data scientists or managers. Demonstrates sound judgement in prioritising tasks and managing time effectively.
Communicates findings and technical concepts clearly to team members and stakeholders. Prepares visualisations and reports that make data accessible to non-technical audiences. Listens actively to feedback and adapts communication style as needed. Participates in meetings and workshops to share progress and learn from others.
Contributes ideas for improving data processes, reporting, and modelling approaches. Stays up to date with emerging tools and techniques in data science. Participates in brainstorming sessions and pilots new solutions under supervision, helping to drive continuous improvement within the team.
Professional Qualification(s)
A degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering is preferred. Certifications in data science, analytics, or relevant programming languages (e.g., Python, R) are advantageous but not essential.
Knowledge
- Understanding of statistical concepts and data analysis techniques.
- Familiarity with data manipulation and visualisation tools (e.g., Python, R, SQL, Excel, Tableau).
- Awareness of machine learning fundamentals and common algorithms.
- Knowledge of data governance and privacy standards (e.g., GDPR).
Skills/Ability
- Analytical thinking and problem-solving skills.
- Ability to work with large datasets and perform data cleaning and transformation.
- Programming skills in Python or R.
- Experience with data visualisation tools (e.g., Tableau, Power BI, Matplotlib).
- Strong attention to detail and accuracy.
- Willingness to learn and adapt to new technologies.
- Effective communication and presentation skills.
- Ability to work collaboratively in a team environment.
- Time management and organisational skills.
Junior Data Scientist - Remote, Dashboards & Insights in Milton Keynes employer: hackajob
Dominos Pizza UK & Ireland is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Junior Data Scientist role. With opportunities for professional growth and development, employees are encouraged to continuously learn and apply new data science techniques while working remotely from locations like Milton Keynes or Manchester. The company values data-driven decision-making, ensuring that your contributions directly impact customer experiences and commercial success.
StudySmarter Expert Advice🤫
We think this is how you could land Junior Data Scientist - Remote, Dashboards & Insights in Milton Keynes
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, predictive models, and dashboards. This is your chance to demonstrate what you can do beyond just a CV—make it visually appealing and easy to navigate.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Get comfortable explaining your thought process and how you tackle data challenges. Remember, it's all about showing your problem-solving skills!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Junior Data Scientist - Remote, Dashboards & Insights in Milton Keynes
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Junior Data Scientist role. Highlight relevant skills like data analysis, programming in Python or R, and any experience with data visualisation tools. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Be sure to mention any specific projects or experiences that relate to the responsibilities listed in the job description.
Showcase Your Projects:If you've worked on any data science projects, whether in school or on your own, make sure to include them! We love seeing practical applications of your skills, so share links to your GitHub or any dashboards you've created.
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 makes it easier for us to keep track of all the amazing candidates like you!
How to prepare for a job interview at hackajob
✨Know Your Data Tools
Familiarise yourself with the data manipulation and visualisation tools mentioned in the job description, like Python, R, SQL, and Tableau. Be ready to discuss your experience with these tools and how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data-related challenges, such as dealing with missing values or outliers. Highlight your logical reasoning and any creative approaches you've taken to improve model accuracy.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You might be asked to present findings to non-technical stakeholders, so being able to convey your insights clearly is crucial. Use visuals if possible to make your points more accessible.
✨Stay Updated on Trends
Demonstrate your commitment to continuous learning by discussing recent trends or tools in data science. Mention any new techniques or best practices you've explored, showing that you're proactive about improving your skills and knowledge.
