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- Tasks: Join a dynamic team as a Data Scientist, analyzing data and building predictive models.
- Company: Work with a leading organization known for innovation in their field.
- Benefits: Enjoy a competitive salary, private health care, and flexible working options.
- Why this job: Make an impact with data-driven decisions and collaborate on cutting-edge projects.
- Qualifications: Proven experience in data science, strong programming skills, and excellent communication abilities.
- Other info: Opportunities for career growth and development in a collaborative environment.
The predicted salary is between 60000 - 80000 £ per year.
Salary: £60,000 – £80,000 per year + Bonus
Private Health-care
Generous Bonus Scheme
Flexible Working Options (Remote/Hybrid)
About the Role:
My client is a leading organisation in their field, and they are looking for a talented Data Scientist to join their growing team. This is a fantastic opportunity for someone with strong analytic skills, a passion for extracting insights from complex data-sets, and a drive to make data-driven decisions that can shape business strategies.
Key Responsibilities:
- Data Analysis & Modelling: Utilise statistical and machine learning techniques to build predictive models and extract insights from large data-sets.
- Data Exploration: Analyse and explore diverse data-sets, identifying patterns, trends, and anomalies to inform business decisions.
- Collaboration: Work closely with stakeholders, including product, engineering, and business teams, to understand data needs and provide actionable insights.
- Data Visualisation: Create clear, informative visualisations to communicate insights and findings to non-technical audiences.
- Algorithm Development: Develop and implement algorithms to automate processes and improve business operations.
- Optimisation: Continuously optimise existing models and processes to improve performance and accuracy.
- Cloud Platforms: Leverage cloud platforms like AWS, GCP, or Azure for data storage, processing, and analysis.
Skills & Experience:
- Proven experience as a Data Scientist or in a similar analytic role.
- Strong proficiency in programming languages like Python, R, or SQL.
- Experience with machine learning techniques, including supervised and unsupervised learning, and deep learning.
- Proficiency in data analysis libraries such as pandas, numpy, scikit-learn, or TensorFlow.
- Familiarity with data visualisation tools (e.g., Tableau, Power BI, Matplotlib).
- Experience working with cloud platforms (AWS, Azure, GCP) and big data technologies.
- Excellent communication skills, with the ability to present complex data findings in a clear and understandable way to both technical and non-technical stakeholders.
- Strong problem-solving skills and the ability to think analytically and creatively.
Preferred Qualifications:
- Experience with big data processing tools such as Spark or Hadoop.
- Familiarity with natural language processing (NLP) or time-series forecasting.
- Experience with A/B testing and experimentation frameworks.
- Knowledge of data engineering concepts and ETL processes.
Why Join My Client?
- Competitive salary (£60,000 – £80,000) with performance-based bonuses.
- Comprehensive private health-care plan.
- Generous benefits package including flexible working options.
- A dynamic, collaborative team with opportunities for career growth and development.
- The chance to work on cutting-edge data science projects in an innovative environment.
If you are passionate about using data to drive business success and are ready to take your career to the next level, apply now.
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Data Scientist 80k employer: TieTalent
Contact Detail:
TieTalent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist 80k
✨Tip Number 1
Make sure to showcase your experience with statistical and machine learning techniques. Highlight specific projects where you've built predictive models or extracted insights from large data sets, as this is crucial for the role.
✨Tip Number 2
Familiarize yourself with the cloud platforms mentioned in the job description, like AWS, GCP, or Azure. If you have hands-on experience, be ready to discuss how you've leveraged these platforms for data storage and analysis.
✨Tip Number 3
Prepare to demonstrate your data visualization skills. Think of examples where you've created clear and informative visualizations to communicate complex data findings to non-technical audiences.
✨Tip Number 4
Collaboration is key in this role, so be ready to share experiences where you've worked closely with cross-functional teams. Highlight how you’ve understood their data needs and provided actionable insights.
We think you need these skills to ace Data Scientist 80k
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Focus on your proficiency in programming languages like Python, R, or SQL, and any experience with machine learning techniques.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your ability to extract insights from complex data sets. Mention specific projects or experiences that demonstrate your analytical skills and problem-solving abilities.
Highlight Collaboration Skills: Since the role involves working closely with various stakeholders, emphasize your collaboration skills in both your CV and cover letter. Provide examples of how you've successfully communicated complex data findings to non-technical audiences.
Showcase Data Visualisation Experience: Include any experience you have with data visualisation tools like Tableau or Power BI. Mention specific instances where your visualisations helped inform business decisions or improved understanding among team members.
How to prepare for a job interview at TieTalent
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples of how you've used data analysis and modeling in your previous roles. Highlight any predictive models you've built and the insights you've extracted from complex datasets.
✨Demonstrate Collaboration Experience
Since collaboration is key in this role, share experiences where you've worked closely with stakeholders from different teams. Explain how you understood their data needs and provided actionable insights that influenced business decisions.
✨Communicate Clearly
Practice explaining complex data findings in a simple and understandable way. You might be asked to present your insights to non-technical audiences, so being able to communicate effectively is crucial.
✨Familiarize Yourself with Cloud Platforms
Make sure you understand how to leverage cloud platforms like AWS, GCP, or Azure for data storage and processing. Be ready to discuss any relevant experience you have with these technologies and how they can enhance data analysis.
