At a Glance
- Tasks: Research and develop intelligent data-driven features using big data in the maritime industry.
- Company: Join a forward-thinking company at the forefront of data science and maritime innovation.
- Benefits: Fully remote role with competitive salary and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and development.
- Why this job: Make an impact by applying machine learning to real-world challenges in a dynamic field.
- Qualifications: Experience in data science, machine learning, and big data tools like Hadoop and Spark.
The predicted salary is between 50000 - 70000 £ per year.
As a data scientist you will be responsible for keeping up to date with the latest big data research in the maritime industry and applying this and your data science knowledge to build intelligent data driven features. It’s an exciting role that requires the analysis of different types of geospatial datasets, with many different potential applications of machine learning. The role is suited to a data scientist who also has a keen interest in data engineering as you will be contributing to the design and development of systems to support data processing and analysis.
The Role
- Research ideas and keep up to date with developments in the big data and transport industry.
- Use analytical techniques including machine learning to develop new data driven features.
- Improve existing algorithms and models.
- Conduct analyses to assist the business with operational questions or to produce insights that can improve our product.
- Aid with onboarding and analysis of new datasets.
- Contribute to the design and maintenance of the data infrastructure allowing us to process, store and analyse data.
- Liaise with our architectural team to ensure that features developed in the research environment can be integrated into our product.
- Collaborate with the development team to operationalise new algorithms, models etc.
Skills, Experiences and Qualities
- Experience of working with multiple stakeholders in taking a solution from an idea to gathering requirements and implementation.
- Must have a can-do attitude.
- Understanding of machine learning and statistical techniques (k-NN, Naive Bayes, SVM, Random Forests, neural networks etc.).
- Experience with big data tools such as Hadoop and Spark.
- Knowledge of different databases and storage solutions including SQL and NoSQL.
- Knowledge of different technologies to build a scalable data infrastructure such as Kafka, Rabbit, Docker and Airflow are desirable.
- Data analysis skills using R or Python.
- Data visualisation skills such as Tableau/Power BI.
- Geospatial analysis skills would be useful.
- Experience with AWS (S3/EMR/Athena/Glue) would be useful.
This will be a fully remote role.
Data Scientist in London employer: Swiftsource
As a leading player in the maritime industry, we pride ourselves on fostering a dynamic and innovative work culture that empowers our data scientists to thrive. With a fully remote setup, we offer flexibility and a collaborative environment where continuous learning and professional growth are at the forefront, alongside competitive benefits that support your well-being and career aspirations.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the maritime and data science fields on LinkedIn. Join relevant groups, participate in discussions, and don’t hesitate to ask for informational interviews. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving machine learning and geospatial analysis. Use platforms like GitHub to share your code and visualisations. This will give potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data science interview questions and be ready to discuss your past projects. Remember, they want to see how you think and approach challenges!
✨Tip Number 4
Don’t just apply anywhere—apply through our website! We’re always on the lookout for passionate data scientists who are eager to make an impact. Tailor your application to highlight your interest in big data and the maritime industry, and let us know why you’d be a great fit!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Your Passion for Data:When you're writing your application, let your enthusiasm for data science and the maritime industry shine through. We want to see that you’re not just ticking boxes but genuinely excited about using your skills to make a difference.
Tailor Your Application:Make sure to customise your CV and cover letter to highlight relevant experiences and skills that match the job description. We love seeing how your background aligns with our needs, especially in machine learning and big data tools.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and how you can contribute to our team.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Swiftsource
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning techniques and big data tools. Be ready to discuss how you've used algorithms like k-NN or Random Forests in past projects. It’s all about showing that you can apply your knowledge practically!
✨Stay Updated on Industry Trends
Since the role involves keeping up with the latest in big data and the maritime industry, do some research before your interview. Bring up recent developments or case studies that excite you, and show how they could relate to the company’s work.
✨Show Off Your Collaboration Skills
This job requires working with multiple stakeholders, so be prepared to share examples of how you've successfully collaborated in the past. Highlight any experience you have liaising with teams to turn ideas into actionable solutions.
✨Demonstrate Your Problem-Solving Mindset
With a can-do attitude being essential, think of specific challenges you've faced in data analysis or engineering and how you overcame them. This will help illustrate your proactive approach and ability to tackle operational questions effectively.
