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- Tasks: Transform data into actionable insights using AI and machine learning.
- Company: Join Supplement Factory, a leader in innovative data solutions.
- Benefits: Competitive salary, pension scheme, 22 days holiday, and career growth opportunities.
- Other info: Dynamic role with potential to lead your own team in the future.
- Why this job: Make a real impact by revolutionising business efficiency with your data skills.
- Qualifications: 3+ years in data science, expertise in Python, R, or SQL required.
The predicted salary is between 29000 - 41000 £ per year.
Supplement Factory is in search of a Data Scientist to transform our business landscape through AI and machine learning. Your primary responsibility will be to create, deploy, and maintain machine learning and AI models that delve into data problems with high levels of accuracy. Your models will revolutionise various departments across the business, driving them towards greater efficiency. In this role, you will work on diverse projects, such as creating AI models that swiftly compute and interpret masses of data related to ingredient interactions, compliance, pricing, and manufacturing capabilities. You will be responsible for turning raw data into actionable insights that significantly impact the bottom line.
Key Responsibilities
- Collaborate with departments across the company to identify and frame key business challenges that can be solved using data.
- Build and deploy machine learning and AI models that interpret various data sets like complex staff rotas, training matrices, HR data, stock data, regulatory data, and sales and marketing data, among others.
- Employ advanced data visualisation techniques.
Technical Skills
- Expertise in programming languages suitable for data science tasks, such as Python, R, or SQL.
- Strong experience in data manipulation, statistical methods, and applying machine learning algorithms.
- Proven experience in deploying open source AI models to assist in the interpretation and processing of complex data sets.
- Proficiency in data visualisation tools is a must.
Experience
- Minimum of 3 years of experience in a similar role.
- Experience in manufacturing will be considered a significant asset.
Educational Requirements
- A degree in a relevant field, such as Computer Science, Engineering, Statistics, or Applied Mathematics, is highly recommended.
Benefits
- Company Pension Scheme
- Free Eye Tests
- 22 Days Holiday + Bank Holidays
Performance Metrics
Performance will be primarily measured based on the effectiveness of the models you create.
Career Growth
Opportunities for career advancement are abundant, with the potential to build a team under your supervision in the future.
Job Type
Full-time
Salary
£35,000.00-£45,000.00 per year
Schedule
Monday to Friday
Ability To Commute/relocate
Ashford: reliably commute or plan to relocate before starting work (required)
Work Location
In person
Data Scientist employer: Supplement Factory
Contact Detail:
Supplement Factory Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even local events. The more you chat with folks in data science, the better your chances of hearing about job openings before they hit the market.
✨Show Off Your Skills
Create a portfolio showcasing your projects and models. Use platforms like GitHub to share your code and visualisations. This not only demonstrates your expertise but also gives potential employers a taste of what you can do!
✨Ace the Interview
Prepare for technical interviews by brushing up on your programming skills and machine learning concepts. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning, AI models, and any relevant programming languages like Python or R. We want to see how your skills align 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 at Supplement Factory. Be specific about your past projects and how they relate to the role.
Showcase Your Projects: If you’ve worked on any interesting data projects, don’t forget to mention them! Whether it’s a personal project or something from a previous job, showcasing your ability to solve real-world problems with data will definitely catch our eye.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Supplement Factory
✨Know Your Data Science Stuff
Make sure you brush up on your programming languages like Python, R, and SQL. Be ready to discuss your experience with machine learning algorithms and data manipulation techniques. The more specific examples you can provide about your past projects, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex data problems in the past. Think of specific challenges you've faced and how your models made a difference. Supplement Factory is looking for someone who can turn raw data into actionable insights, so highlight your successes!
✨Get Familiar with Their Business
Do some homework on Supplement Factory and their operations. Understand their products and how data science can impact areas like compliance, pricing, and manufacturing. This will help you frame your answers in a way that shows you're genuinely interested in their business.
✨Practice Your Data Visualisation Skills
Since proficiency in data visualisation tools is a must, be prepared to discuss how you've used these tools in your previous roles. Bring examples of your work if possible, and be ready to explain how your visualisations helped communicate complex data effectively.