Job Description
Capacity Planning Data Scientist
Location: Middlesex (3 days onsite, 2 days from home)
Salary: Negotiable depending on experience
Job Ref: J13078
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
Experience required:
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, data.table, 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.
Datatech is one of the UK's leading recruitment agencies in analytics and the host of the Women in Data event. For more information, visit (url removed)
Location: Middlesex (3 days onsite, 2 days from home)
Salary: Negotiable depending on experience
Job Ref: J13078
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
Experience required:
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, data.table, 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.
Datatech is one of the UK's leading recruitment agencies in analytics and the host of the Women in Data event. For more information, visit (url removed)
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