Remote GenAI Data Scientist — Free Training Included in London

Remote GenAI Data Scientist — Free Training Included in London

London Part-Time 60750 - 74250 £ / year (est.) Home office (partial)
Code First Girls

At a Glance

  • Tasks: Learn and apply Python, NLP, and ML skills in a supportive environment.
  • Company: Code First Girls, empowering women in tech with innovative training.
  • Benefits: Free training, remote learning, and potential job placement as a Data Scientist.
  • Other info: Flexible part-time course with networking opportunities in London or Manchester.
  • Why this job: Kickstart your career in data science with hands-on experience and mentorship.
  • Qualifications: 1.5+ years in tech using Python; must pass coding assessment.

The predicted salary is between 60750 - 74250 £ per year.

Code First Girls is offering a free training course that leads to a Data Scientist role with partner clients. The program is 16 weeks, part-time, designed to build mid-level Python, NLP and ML skills, with remote learning and occasional in-person meetups in London or Manchester. After completing the course, successful participants may join client teams as Data Scientists.

You should have 1.5+ years in a tech role using Python, be able to pass a Python/Java/JavaScript assessment.

Remote GenAI Data Scientist — Free Training Included in London employer: Code First Girls

Code First Girls is an exceptional employer that champions inclusivity and professional growth, making it a rewarding place for experienced Java developers to contribute as technical coaches. With a commitment to addressing gender imbalance in tech, the company fosters a supportive remote work culture that values mentorship and collaboration, offering flexible freelance opportunities that empower coaches to shape the future of aspiring software engineers. Join us in making a meaningful impact while enjoying the freedom of remote work across the UK.

Code First Girls

Contact Details:

Code First Girls Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Remote GenAI Data Scientist — Free Training Included in London

Get Involved in Data Challenges

Participate in data challenges like Kaggle competitions or DrivenData to showcase your skills and network with other data enthusiasts. Not only will you build your portfolio, but you can also catch the eye of potential employers like Code First Girls.

Connect with Local Data Communities

Join local data science meetups or online communities like Data Science Society to engage with professionals in the field. These platforms are great for networking, discovering job opportunities, and keeping your fingers on the pulse of industry trends.

Leverage Your University’s Resources

If you're still in university, make full use of your career services. They might have part-time roles tailored for students like you, and often have direct connections with companies looking to hire talented interns in data science roles.

Apply Directly Through Our Website

Don’t forget to check out our jobs at Code First Girls and apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate individuals like us who are eager to make an impact in the data science world.

We think you need these skills to ace Remote GenAI Data Scientist — Free Training Included in London

Python
SQL
Communication Skills
Problem-Solving Skills
Data Engineering
Attention to Detail
ETL/ELT Processes

Some tips for your application 🫡

Show Your Data Skills:In your CV, make sure to highlight your proficiency with key data analysis tools and programming languages like Python, R, or SQL. We want to see that you've got hands-on experience with data manipulation and visualisation, so if you've worked on any relevant projects or coursework, include those details to really showcase your skills!

Tailor Your Projects Towards Data Science:When it comes to your portfolio, focus on showcasing projects that highlight your data-science abilities. Include analyses, dashboards, or any predictive models you've built. If you've contributed to Kaggle competitions or have a GitHub repository with data projects, make sure to link those—these demonstrate your practical experience and problem-solving abilities.

Express Your Motivation in the Cover Letter:Since this is a part-time role, we want to know why you're particularly interested in juggling this with your other commitments. Use your cover letter to express your passion for data science and how this role at Code First Girls aligns with your career aspirations. Show us you're excited about learning and growing with us!

Keep It Concise Yet Informative:Part-time positions often receive many applications, so keep your documents clear and to the point! Aim for a concise CV detailing your relevant experiences without unnecessary fluff. Be sure to include your availability in your cover letter as well—that helps us in the decision-making process!

How to prepare for a job interview at Code First Girls

Brush Up on Your Stats!

Given you're eyeing a part-time role in data science, make sure you’re on top of your statistical methods and data analysis techniques. Expect questions around regression, hypothesis testing, and maybe even some statistical programming languages like R or Python during the interview with Code First Girls.

Show Off Your Projects!

It's crucial to have a portfolio that showcases your data science projects. Highlight your part-time work with specific data sets, models you've built, or analyses you've conducted. Having tangible examples will demonstrate your hands-on experience and problem-solving skills to Code First Girls.

Familiarise Yourself with Tools of the Trade

Make sure you’re well-versed in data science tools like Jupyter Notebook, Tableau, or SQL. You might get technical questions or even a practical test at Code First Girls, so having a comfort level with these tools will definitely be an advantage.

Be Ready to Discuss Real-World Applications

Since this is a part-time role, employers at Code First Girls will likely appreciate your understanding of how data science can address actual business problems. Be prepared to discuss any relevant case studies or how you would approach specific challenges in real scenarios.