Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Transform legal tech with data science, tackling challenges and driving efficiencies.
- Company: Join a forward-thinking team at the Digital Data Foundation in Belfast.
- Benefits: Excellent salary, benefits, and opportunities for professional growth.
- Why this job: Be at the forefront of innovation, reshaping how legal services are delivered.
- Qualifications: Degree in Data Science with 2+ years of experience; legal knowledge is a plus.
- Other info: Collaborative environment with a focus on cutting-edge technologies.
The predicted salary is between 36000 - 60000 £ per year.
Belfast, Northern Ireland, United Kingdom
About the job
£ Excellent Salary + Benefits - Ireland
James Carrera of Digital Data Foundation has been retained to source a talented Data Scientist to be centric in the application of disruptive technologies for scalable solutions in Legal Technology, to solve challenges & drive efficiencies.
Responsibilities
- With applications in e-discovery, AI, data extraction, data visualisation and workflow, the data scientist will work closely and collaboratively, at the cutting edge of innovation, to change the way legal services are delivered.
- Elicit business objectives or identify challenges and select appropriate tools.
- Work internal and external with clients to understand requirements.
- Design/create data processing pipelines for structured, semi-structured and unstructured sources that aid data exploration and modelling.
- Design/create tools that allow the business to answer specific, relevant questions.
- Develop proofs of concept to assist in business decisions.
- Data cleaning, modelling, reporting, statistical analysis, algorithm development, resource planning.
- Advise, plan, and deliver appropriate solutions to analyse data and interpret results.
Experience
- Educated to degree level you will have at least 2 years progressive experience in Data Science.
- Understanding of legal services, preference given to those with legal experience.
- Standard ETL and/or data analysis languages - R, Python, Scala, SQL.
- Creating software packages/libraries including documentation and tests.
- Understanding of data types, data structures, and notation/markup standards such as JSON and XML.
- Principles of visualisation.
- Knowledge of latest trends in data science, a passion for innovation.
- Exceptional communicator, the ability to explain technical aspects clearly and simply to individuals from varying non-technical backgrounds.
Data Scientist - Legal Technology in Belfast employer: Digital Data Foundation
Contact Detail:
Digital Data Foundation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Legal Technology in Belfast
✨Tip Number 1
Network like a pro! Reach out to folks in the legal tech space on LinkedIn or at industry events. We can’t stress enough how personal connections can open doors that applications alone can’t.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those relevant to legal technology. We love seeing real-world applications of your work, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and legal tech scenarios. We recommend practising with friends or using mock interview platforms to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who want to make a difference in legal tech.
We think you need these skills to ace Data Scientist - Legal Technology in Belfast
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role in Legal Technology. Highlight your experience with data processing pipelines, AI, and any relevant legal knowledge. We want to see how your skills align with our needs!
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 innovative solutions in legal tech. Keep it engaging and personal – we love a good story!
Showcase Your Projects: If you've worked on any relevant projects, make sure to showcase them! Whether it's data visualisation or algorithm development, we want to see your hands-on experience. Include links or descriptions that demonstrate your skills.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Digital Data Foundation
✨Know Your Data Science Tools
Make sure you’re well-versed in the standard ETL and data analysis languages mentioned in the job description, like R, Python, Scala, and SQL. Brush up on your knowledge of data types and structures, as well as visualisation principles, so you can confidently discuss how you would apply these tools in a legal tech context.
✨Understand the Legal Landscape
Since this role is centred around legal technology, it’s crucial to have a grasp of the legal services sector. Familiarise yourself with common challenges faced in this field and think about how data science can provide solutions. This will show your potential employer that you’re not just a tech whiz but also understand the industry’s needs.
✨Prepare for Scenario-Based Questions
Expect to be asked about specific scenarios where you’ve had to elicit business objectives or tackle challenges using data science. Prepare examples from your past experience where you successfully designed data processing pipelines or developed proofs of concept. This will demonstrate your practical skills and problem-solving abilities.
✨Communicate Clearly and Confidently
As an exceptional communicator, you’ll need to explain complex technical concepts to non-technical stakeholders. Practice articulating your thoughts clearly and simply. You might even want to prepare a few examples of how you’ve done this in the past, as it will highlight your ability to bridge the gap between data science and business needs.
