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For Companies At a Glance
- Tasks: Create advanced algorithms and predictive models to solve real-world problems.
- Company: Join a forward-thinking tech company focused on innovative data solutions.
- Benefits: Enjoy competitive pay, health perks, and opportunities for professional growth.
- Why this job: Make an impact with your skills in a dynamic, collaborative environment.
- Qualifications: Bachelor's in STEM, strong maths background, and experience in Python and R.
- Other info: Hybrid working model with a vibrant office culture and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
As a Data Scientist, you will develop sophisticated algorithms and predictive models, leveraging a broad spectrum of techniques from mathematical and statistical methods to advanced machine learning approaches. You will be working alongside DevOps and software development teams to ensure seamless integration and efficacy of your models to our clients' software to deliver mission-critical communications solutions for customers. This is an office-based vacancy and as such we expect all applicants to be willing to commute to our offices a minimum of 3-4 days per week as per our hybrid working policy.
Key Responsibilities
- Craft and refine predictive models using a diverse array of methods, including but not limited to linear programming, heuristic algorithms, and machine learning techniques.
- Solve complex problems using statistical techniques and data analysis.
- Stay abreast of current research and integrate relevant findings into your work.
- Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods.
- Develop algorithms and code, primarily using Python and R, and integrate these into our products.
- Conduct research to develop prototypes and proof of concepts.
- Work within an agile team to develop applications to meet product/customer requirements.
- Thoroughly test algorithms or developments to make sure they perform the desired task correctly in all cases.
- Work with Quality Assurance teams/processes to validate builds ready for launch.
- Problem solve and fix bugs as discovered/reported.
- Address and resolve any issues that arise post-deployment.
- Perform ongoing maintenance or upgrade of the platform as required, following internal change procedures at all times.
- Share ideas and work on projects for improving applications, process or the wider platform.
- Review projects/deployments and learn lessons to improve future performance.
- Stay up to date with data science literature and technological advancements. Learn and test new technologies, frameworks, research papers and languages as relevant.
About You
- Bachelor's Degree in a STEM subject, preferably from a Russell Group University.
- Strong mathematical and statistical background; expertise in Python and R, including libraries like Numpy, Pandas, Pytorch and Scikit-learn.
- Demonstrable experience in data science and a proven track record in developing predictive models.
- Experience contributing to a software project/product.
- Experience with databases.
- A post-graduate degree in Data Science or a related field.
- Experience with source control, in particular Git.
- Experience working within an agile environment, in particular Scrum, and applying supporting practices.
- Experience with C# and Microsoft SQL Server.
- Good experience in database technologies, such as Microsoft SQL Server.
- Experience in developing containerising applications with Docker and using orchestration such as Kubernetes.
Data Scientist in London employer: JAM IT Consultancy Ltd
Contact Detail:
JAM IT Consultancy Ltd Recruiting Team
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 your connections in the data science field, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and algorithms. Use platforms like GitHub to share your code and projects, making it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and problem-solving abilities. Practice common data science interview questions and be ready to discuss your past projects in detail. We want to see how you think!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect with us directly. Don’t miss out on this opportunity!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, R, and any predictive models you've developed. We want to see how your skills match up with what we're looking for!
Showcase Your Projects: Include any relevant projects or prototypes you've worked on. Whether it's a personal project or something from your studies, we love seeing practical applications of your skills. It gives us a glimpse into your problem-solving abilities!
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 our team. We appreciate a bit of personality, so don’t be afraid to let your enthusiasm show!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at JAM IT Consultancy Ltd
✨Know Your Algorithms
Brush up on your knowledge of algorithms and predictive models. Be ready to discuss specific techniques you've used, like linear programming or machine learning methods. Prepare examples of how you've applied these in real-world scenarios.
✨Showcase Your Coding Skills
Since Python and R are key for this role, practice coding challenges beforehand. Be prepared to write code during the interview or explain your thought process behind your coding decisions. Familiarity with libraries like Numpy and Pandas will definitely give you an edge.
✨Understand Agile Methodologies
Familiarise yourself with agile practices, especially Scrum. Be ready to discuss your experience working in agile teams and how you’ve contributed to projects. Highlight any specific roles you’ve played in sprints or retrospectives.
✨Stay Current with Data Science Trends
Demonstrate your passion for data science by discussing recent research or technological advancements you've explored. Mention any new frameworks or languages you're testing out, as this shows your commitment to continuous learning and improvement.
