At a Glance
- Tasks: Design machine learning models and optimise capacity in a fast-paced logistics environment.
- Company: Join a market-leading global logistics organisation with a focus on innovation.
- Benefits: Negotiable salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative culture with a proactive approach to problem-solving.
- Why this job: Make a real impact by applying data science to complex operational challenges.
- Qualifications: Master's degree in a quantitative field and strong experience with large datasets.
The predicted salary is between 50000 - 60000 £ per year.
A market leading global logistics organisation is seeking a highly motivated Airline Capacity Planning Data Scientist who wants to apply their work in a real, high impact environment. Your work will directly influence how capacity is planned, optimised, and delivered within a complex, high volume operational setting. This role sits at the intersection of data science and operations research, with a strong focus on simulation, modelling, and real world system optimisation.
You will work with large scale datasets to build machine learning models and develop advanced simulation tools that support critical planning decisions.
The role:- Design and build machine learning models to forecast demand, utilisation and system performance
- Work with large scale, time series datasets to engineer features and improve model accuracy
- Apply robust validation, tuning and model selection techniques to deliver reliable outputs
- Build and calibrate discrete event simulation (DES) models of complex operational systems to stress test capacity under different demand scenarios
- Carry out scenario analysis and what if modelling to support planning and investment decisions
- Translate complex analytical outputs into clear, actionable insights for operational stakeholders
- Develop tools and dashboards to monitor system performance and support decision making
- Work closely with operational teams to ensure models reflect real world constraints and behaviours
- Master's degree (or equivalent) in Data Science, Statistics, Operations Research, Computer Science, Mathematics, or a closely related quantitative discipline
- Strong experience in a Data Scientist or Operational Research focused role working with large, complex datasets
- Solid understanding of machine learning techniques such as gradient boosting, random forests and time series modelling
- Experience building and deploying models used in real world decision making (e.g. ensemble methods, regularised regression)
- Advanced proficiency in R, including tidyverse, caret or tidymodels, xgboost and Shiny
- Strong SQL skills with experience querying large scale relational databases such as Azure SQL or PostgreSQL
- Experience working with high volume or time based data, including feature engineering
- Experience with simulation, discrete event simulation, or operations research techniques is highly desirable
- Ability to communicate complex analysis clearly to non-technical stakeholders
- Comfortable working in fast paced, operational environments
- Proactive, hands on approach with the ability to take ownership of problems end to end
If you want to work on complex systems where your output is actually used and matters, this is a genuinely strong opportunity to do that. Please note we can only accept applications from those with current and full UK working rights for this role, as sponsorship is not available. If this sounds like the role for you then please apply today. Alternatively, you can refer a friend or colleague through our referral scheme. For each successful placement, you will be eligible for our reward scheme with no limit on referrals.
Capacity Planning Data Scientist in England employer: Datatech Analytics
Join a market-leading global logistics organisation in Middlesex as a Capacity Planning Data Scientist, where your expertise will directly impact operational efficiency and decision-making. Enjoy a flexible work culture with three days onsite and two days from home, alongside opportunities for professional growth through hands-on experience with large datasets and advanced modelling techniques. With a commitment to innovation and collaboration, this role offers a unique chance to contribute to high-stakes projects in a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Capacity Planning Data Scientist in England
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in capacity planning or data science. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving machine learning models or simulation tools. Share it on platforms like GitHub or LinkedIn. This gives potential employers a taste of what you can do and how you approach real-world problems.
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies related to capacity planning. Be ready to discuss your past experiences and how they relate to the role. Remember, it’s not just about technical skills; show your passion for solving complex problems!
✨Apply Through Our Website
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 and take the initiative to reach out directly.
We think you need these skills to ace Capacity Planning Data Scientist in England
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Capacity Planning Data Scientist. Highlight your experience with machine learning, data analysis, and any relevant projects that showcase your skills in a real-world context.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background aligns with the job description. Don’t forget to mention your experience with large datasets and simulation techniques.
Showcase Your Technical Skills:Be specific about your technical skills in your application. Mention your proficiency in R, SQL, and any other tools you’ve used. This will help us see how you can hit the ground running in our fast-paced environment.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Datatech Analytics
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning techniques, especially gradient boosting and time series modelling. Be ready to discuss how you've applied these in real-world scenarios, as this role is all about using data science to make impactful decisions.
✨Showcase Your Simulation Skills
Since the job involves building discrete event simulation models, be prepared to talk about any experience you have with simulation techniques. If you can share examples of how you've stress-tested capacity under different demand scenarios, that’ll definitely impress them!
✨Communicate Clearly
This role requires translating complex analytical outputs into actionable insights for non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the impact of your work rather than just the technical details.
✨Be Proactive and Hands-On
Demonstrate your proactive approach by discussing times when you took ownership of a problem from start to finish. They’re looking for someone who can thrive in fast-paced environments, so share examples that highlight your ability to adapt and take initiative.
