At a Glance
- Tasks: Explore and analyse data to develop insights and practical solutions for clients.
- Company: AWTG, a forward-thinking company focused on data-driven solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on ethical data practices and career advancement.
- Why this job: Join a dynamic team and make a real impact using data science and machine learning.
- Qualifications: Experience in data science, proficiency in Python or R, and strong communication skills.
The predicted salary is between 45000 - 55000 £ per year.
The Data Scientist will use data science, statistics and machine learning techniques to generate insight and develop practical solutions for AWTG and its clients. The role works with multidisciplinary teams to explore data, build models and communicate findings clearly. You will work with multidisciplinary teams across data, AI, software engineering, product, QA and delivery to create practical outcomes for clients and end users.
Key responsibilities
- Explore, prepare, analyse and visualise data to identify patterns, trends and opportunities.
- Develop data science outputs such as models, reports, dashboards, forecasts or decision-support tools.
- Apply appropriate statistical, machine learning or analytical techniques to solve business or user problems.
- Work with data engineers, analysts, developers and product teams to deliver usable data science solutions.
- Document methods, assumptions, limitations and validation results clearly and responsibly.
- Consider data ethics, privacy and security throughout the data science life cycle.
Essential skills and experience
- Experience applying data science or statistical methods to real-world problems.
- Good knowledge of Python, R or similar programming languages for analysis and modelling.
- Understanding of machine learning, statistical testing, model validation and performance metrics.
- Ability to prepare, clean and transform data for analysis and modelling.
- Ability to communicate technical findings and visualisations to non-technical audiences.
- Awareness of data ethics, privacy, bias, model limitations and responsible use of data.
Desirable skills and experience
- Experience with NLP, time series, optimisation, predictive analytics or simulation.
- Experience with cloud data platforms, notebooks, Git, APIs or data pipelines.
- Experience delivering data science outputs within Agile or multidisciplinary teams.
What success looks like
- Data science outputs are valid, explainable and aligned to business needs.
- Models and analysis are documented, tested and communicated clearly.
- Insights help teams improve services, operations or decision-making.
Data Scientist employer: AWTG Ltd
As a leading employer in the data science field, we offer a dynamic remote work environment that fosters collaboration across multidisciplinary teams. Our commitment to employee growth is evident through mentorship opportunities and a focus on responsible AI practices, ensuring that our team members not only excel in their roles but also contribute to meaningful outcomes for clients. Join us to be part of a culture that values innovation, ethical practices, and the continuous development of your skills.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to professionals in the data science field on LinkedIn or at local meetups. We can’t stress enough how valuable personal connections can be when it comes to landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, models, and visualisations. This is your chance to demonstrate your expertise and creativity, so make sure it’s easily accessible for potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. We recommend practising with friends or using mock interview platforms to get comfortable discussing your methods and findings.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented data scientists like you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with data science and machine learning techniques. We want to see how you've tackled real-world problems, so don’t hold back on those examples!
Showcase Your Skills:Include specific programming languages like Python or R in your application. We’re keen on seeing your technical prowess, so mention any relevant projects or tools you’ve used that align with our needs.
Communicate Clearly:When writing your cover letter, keep it straightforward and engaging. We love candidates who can explain complex ideas simply, especially when it comes to communicating findings to non-technical audiences.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at AWTG Ltd
✨Know Your Data Science Stuff
Make sure you brush up on your data science techniques, especially those related to machine learning and statistical methods. Be ready to discuss how you've applied these skills in real-world scenarios, as this will show your practical experience.
✨Show Off Your Communication Skills
Since you'll need to explain complex findings to non-technical audiences, practice simplifying your explanations. Prepare examples of how you've communicated technical results in the past, and be ready to demonstrate your ability to visualise data effectively.
✨Collaborate Like a Pro
This role involves working with multidisciplinary teams, so highlight your teamwork experiences. Think of specific projects where you collaborated with data engineers, analysts, or product teams, and be prepared to discuss how you contributed to successful outcomes.
✨Be Ethical and Responsible
Familiarise yourself with data ethics, privacy, and security issues. Be ready to discuss how you consider these factors in your work, and provide examples of how you've documented your methods and validated your results responsibly.
