At a Glance
- Tasks: Transform complex data into actionable insights and build impactful machine learning models.
- Company: Established business with a strong focus on data and digital capabilities.
- Benefits: Salary up to £60,000, hybrid work, and professional development opportunities.
- Other info: Collaborate with cross-functional teams in a supportive environment.
- Why this job: Make a real commercial impact while growing your data science skills.
- Qualifications: Degree in relevant field and 2+ years of data analysis experience.
The predicted salary is between 60000 - 60000 £ per year.
We've partnered with a large, established business to find a Data Scientist who will help translate complex data into insights that drive real commercial decisions. This is an organisation with significant scale and a growing focus on data and digital capability. You'll sit within a dedicated data function, working closely with a Senior Data Scientist and collaborating across engineering, product and business teams to build models that get used, not just presented.
Responsibilities as a Data Scientist:
- Conduct exploratory data analysis to identify trends, patterns and anomalies across large datasets
- Build, refine and deploy machine learning models to solve business problems
- Perform data cleaning, feature engineering and transformation to ensure data quality and model suitability
- Monitor deployed model performance and recommend adjustments as needed
- Work with cross-functional teams to translate business needs into data science solutions
Requirements:
- Degree in Computer Science, Mathematics, Engineering or a related discipline
- ~2+ years of experience in data analysis, statistical modelling or data science
- ~ Hands-on experience with Python, R or SQL
- ~ Proven experience with machine learning algorithms and data science methodologies
- ~ Familiarity with cloud platforms, big data technologies and distributed computing
- ~ Experience with data visualisation tools such as Power BI or Tableau is a plus
If you're a Data Scientist looking for a role with solid foundations, real data and room to develop, get in touch.
Marketing Data Scientist employer: Formula.
Join a large, established business in London that prioritises data-driven decision-making and offers a collaborative work culture. As a Marketing Data Scientist, you'll benefit from structured support and mentorship from experienced professionals, alongside opportunities for personal and professional growth within a dedicated data function. With a focus on impactful projects and a hybrid working model, this role provides a unique chance to contribute to meaningful commercial outcomes while advancing your career in a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Marketing Data Scientist
✨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 Formula.!
✨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 Marketing Data Scientist at Formula..
✨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 Formula..
✨Apply Directly through Our Website
When you find a suitable opening like Marketing Data Scientist at Formula., 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 Marketing Data Scientist
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 Formula., 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 Formula.. 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 Formula.
✨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 Formula.!
✨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.
