Applied Data Scientist β€” Flexible Hours & Real-World Impact in London

Applied Data Scientist β€” Flexible Hours & Real-World Impact in London

London Full-Time 45000 - 60000 Β£ / year (est.) No working from home possible
hackajob

At a Glance

  • Tasks: Investigate and deploy advanced data models to transform client data interactions.
  • Company: Join a diverse team at hackajob in Greater London.
  • Benefits: Enjoy flexible hours and a comprehensive rewards package.
  • Other info: Flexible working environment with opportunities for growth.
  • Why this job: Make a real-world impact with your data science skills.
  • Qualifications: Degree in a relevant field and strong programming skills in Python and SQL.

The predicted salary is between 45000 - 60000 Β£ per year.

hackajob is looking for an Applied Data Scientist to join their diverse team in Greater London. In this role, you will investigate and deploy advanced data models, transforming the way clients interact with their data.

The ideal candidate will have a degree in a relevant field and possess strong programming abilities in Python and SQL.

We offer a flexible working environment and a comprehensive rewards package.

Applied Data Scientist β€” Flexible Hours & Real-World Impact in London employer: hackajob

At hackajob, we pride ourselves on being an excellent employer by fostering a flexible working environment that empowers our team to achieve real-world impact through data science. Our diverse culture encourages collaboration and innovation, while our comprehensive rewards package and commitment to employee growth ensure that you can thrive both personally and professionally in the vibrant setting of Greater London.

hackajob

Contact Details:

hackajob Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Applied Data Scientist β€” Flexible Hours & Real-World Impact in 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 hackajob!

✨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 Applied Data Scientist β€” Flexible Hours & Real-World Impact at hackajob.

✨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 hackajob.

✨Apply Directly through Our Website

When you find a suitable opening like Applied Data Scientist β€” Flexible Hours & Real-World Impact at hackajob, 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 Applied Data Scientist β€” Flexible Hours & Real-World Impact in London

Data Modelling
Python
SQL
Analytical Skills
Problem-Solving Skills
Data Transformation
Communication Skills

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 hackajob, 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 hackajob. 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 hackajob

✨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 hackajob!

✨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.