At a Glance
- Tasks: Build data-driven models to boost sales and identify growth opportunities.
- Company: Join a global tech organisation with a focus on innovation.
- Benefits: £500/day, hybrid working, and a chance to influence business strategy.
- Other info: Initial 6-12 month contract with excellent career development potential.
- Why this job: Make a real impact by analysing complex datasets and delivering insights.
- Qualifications: 5+ years SQL experience and skills in predictive modelling required.
The predicted salary is between 72000 - 108000 £ per year.
We are currently seeking a Data Science Engineer to join a global technology organisation on a contract basis. This role will focus on building data-driven models to identify growth opportunities and improve sales performance across a large customer base. Working closely with senior stakeholders, you will analyse complex datasets, build predictive models, and deliver insights that directly influence business strategy and sales campaigns.
Key skills required:
- Strong SQL experience (5+ years) working with complex datasets
- Experience building and deploying data science / predictive models
- Experience with customer segmentation, forecasting, or propensity modelling
- Strong stakeholder communication skills
- Python and Databricks experience desirable
Contract Details:
- £500 per day (Inside IR35)
- London / Hybrid working
- Initial 6-12 month contract
Data Science Engineer - £500 a day (Inside IR35) - London employer: Salt
Join a forward-thinking investment management platform in London, where innovation meets opportunity. As a Senior Business Analyst, you'll thrive in a collaborative work culture that values your expertise and encourages professional growth through continuous learning and development. Enjoy the flexibility of a hybrid working model while contributing to cutting-edge AI-driven investment solutions that make a real impact in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Engineer - £500 a day (Inside IR35) - London
✨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 Salt!
✨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 Data Science Engineer - £500 a day (Inside IR35) - London at Salt.
✨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 Salt.
✨Apply Directly through Our Website
When you find a suitable opening like Data Science Engineer - £500 a day (Inside IR35) - London at Salt, 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 Data Science Engineer - £500 a day (Inside IR35) - London
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 Salt, 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 Salt. 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 Salt
✨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 Salt!
✨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.
