Transport Data Scientist: Modelling & ML

Transport Data Scientist: Modelling & ML

Full-Time 60750 - 74250 £ / year (est.) Home office (partial)
J

At a Glance

  • Tasks: Transform transport data into insights and apply ML/AI for travel demand modelling.
  • Company: Join Jacobs, a leader in data and analytics with a global reach.
  • Benefits: Hybrid work model, competitive salary, and opportunities for career growth.
  • Other info: Collaborate with a global team of experts in a dynamic environment.
  • Why this job: Make a real impact on high-profile transport projects using cutting-edge technology.
  • Qualifications: Experience in data science, machine learning, and strong analytical skills.

The predicted salary is between 60750 - 74250 £ per year.

Jacobs is seeking an experienced Transport Data Scientist to join its growing data and analytics capability. You will transform large transport datasets into insights, apply ML/AI to model travel demand, and collaborate with a global team of experts to deliver data-driven solutions for high-profile transport projects in the UK and internationally.

You will work in a hybrid model, shaping innovative modelling approaches, with opportunities for technical leadership and career growth.

Transport Data Scientist: Modelling & ML employer: Jacobs

At Jacobs, we pride ourselves on being an exceptional employer, offering a dynamic and inclusive work culture that prioritises safety, integrity, and collaboration. Our Glasgow office provides flexible working arrangements and a wealth of opportunities for professional growth, allowing you to contribute to innovative maritime projects while being part of a supportive team that values diverse perspectives. Join us to make a meaningful impact in the world of civil and structural engineering, all while enjoying the benefits of a global network and a commitment to employee well-being.

J

Contact Details:

Jacobs Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Transport Data Scientist: Modelling & ML

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jacobs!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Transport Data Scientist: Modelling & ML at Jacobs.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jacobs.

Apply Directly through Our Website

When you find a suitable opening like Transport Data Scientist: Modelling & ML at Jacobs, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Transport Data Scientist: Modelling & ML

Data Transformation
Machine Learning (ML)
Artificial Intelligence (AI)
Modelling Techniques
Data Analysis
Collaboration Skills
Technical Leadership

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Jacobs, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jacobs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Jacobs

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jacobs!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.