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For Companies At a Glance
- Tasks: Dive into data, clean it up, and help build predictive models.
- Company: Join a forward-thinking team that values learning and collaboration.
- Benefits: Enjoy flexible working options and a competitive salary package.
- Why this job: Kickstart your data science career and make an impact from day one.
- Qualifications: Degree in a quantitative field or equivalent experience; basic Python knowledge preferred.
- Other info: Great opportunities for career growth and continuous learning.
The predicted salary is between 28800 - 48000 £ per year.
At Why Hiring, we believe in the power of connecting talented individuals with incredible remote job opportunities. Our mission is to simplify the job search process and empower professionals to find fulfilling roles that align with their skills and passions, regardless of geographical constraints.
In this role as a Junior Data Scientist, you’ll collaborate with data experts and various teams across the organization to explore data, create predictive models, and uncover insights that shape key business strategies.
Key Responsibilities:
- Develop, configure, and test informatics and data science solutions for diverse technical applications, while providing ongoing support.
- Utilize analytical techniques to diagnose data-related issues, implement effective solutions, and evaluate outcomes.
- Prepare and present comprehensive documentation, design alternatives, and findings to team members and clients.
- Develop strategic data modeling processes, with an emphasis on accurately identifying cause-and-effect relationships.
- Work with tools for data integration, visualization, mining, and analysis, while ensuring compatibility across integrated development environments.
- Manage and enhance shared libraries and tools used across multiple teams.
Qualifications:
- Bachelor’s degree with 1-3 years of experience, or a Master’s degree with similar experience.
- Proficiency in machine learning (ML) areas such as natural language processing, computer vision, and statistical learning theory.
- Proven experience in an ML engineering or data scientist role, building and optimizing ML models.
- Strong coding skills in Python, R, Scala, Java, or C++
- Experience working with large-scale datasets, uncovering hidden patterns, using data visualization tools, writing SQL, and leveraging GPUs for model development.
- Skilled in communicating technical concepts to a variety of audiences, including business, technical, and non-technical stakeholders, with experience delivering data-driven presentations.
Junior Data Scientist employer: Why Hiring
Contact Detail:
Why Hiring Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to professionals in the data science field on LinkedIn or at local meetups. Don’t be shy; ask for informational interviews to learn more about their experiences and get advice on breaking into the industry.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, or data visualisations. This will give potential employers a taste of what you can do and set you apart from other candidates.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as communication is key when presenting insights to both technical and non-technical folks.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for eager learners like you. Keep an eye on our job postings and make sure to tailor your application to highlight your analytical mindset and willingness to grow.
We think you need these skills to ace Junior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your analytical skills and any relevant experience with data science tools. We want to see how your background fits the Junior Data Scientist role, so don’t be shy about showcasing your projects or coursework!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and enthusiasm for the role. Share why you’re excited about data science and how you plan to grow in this field. Let us know what makes you a great fit for our team!
Showcase Your Learning Mindset: We love candidates who are eager to learn! Mention any online courses, workshops, or personal projects you've undertaken to improve your skills in Python, SQL, or data visualisation. This shows us you're proactive and ready to dive into new challenges.
Apply Through Our Website: To make sure your application gets to us directly, apply through our website. It’s the easiest way for us to review your materials and get you into the process. Plus, it shows you’re serious about joining the StudySmarter team!
How to prepare for a job interview at Why Hiring
✨Know Your Data Tools
Make sure you brush up on your knowledge of Python and SQL before the interview. Familiarise yourself with libraries like pandas and scikit-learn, as well as basic SQL queries. Being able to discuss these tools confidently will show that you're ready to dive into the role.
✨Show Your Analytical Mindset
Prepare to discuss how you've approached problem-solving in the past. Think of specific examples where you've cleaned or analysed data, even if it was during your studies or personal projects. This will demonstrate your analytical skills and eagerness to learn.
✨Communicate Clearly
Practice explaining complex concepts in simple terms. You might be asked to present insights from a project or explain a model you've worked on. Being able to communicate effectively with both technical and non-technical audiences is key in this role.
✨Embrace a Growth Mindset
Be ready to talk about how you handle feedback and your desire to learn. Share examples of how you've improved your skills over time or adapted to new challenges. This will highlight your willingness to grow and develop within the company.
