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- Tasks: Analyse complex data to support strategic business decisions and develop machine learning models.
- Company: Join Keller Executive Search, a dynamic team focused on leveraging data for impactful business growth.
- Benefits: Enjoy opportunities for remote work, professional development, and a collaborative team culture.
- Why this job: Make a real impact by transforming data into insights that drive business success.
- Qualifications: Bachelor's in Data Science or related field; experience with Python, R, and machine learning required.
- Other info: Ideal for those passionate about data and eager to learn in a fast-paced environment.
The predicted salary is between 28800 - 48000 £ per year.
Keller Executive Search is currently looking for a talented Data Scientist to join their dynamic team. In this role, you will harness the power of data to derive insights and support key business decisions across a range of strategic initiatives. You will be responsible for utilizing advanced statistical methods, machine learning algorithms, and data visualization techniques to tackle complex data challenges. Your work will involve working with large datasets, conducting analyses, and presenting findings to stakeholders, enabling them to leverage data in their decision-making processes.
Key Responsibilities:
- Analyze and interpret complex data from diverse sources to inform strategic business decisions.
- Develop and implement machine learning models and statistical analyses to solve business challenges.
- Collaborate with cross-functional teams to identify opportunities for leveraging data to drive business growth.
- Visualize data through intuitive dashboards and reports to effectively communicate findings and insights to technical and non-technical stakeholders.
- Stay updated on industry trends and best practices to continuously enhance the team’s analytical capabilities.
- Write clear documentation on methodology, model interpretations, and implementation strategies.
Requirements:
- Bachelor's degree in Data Science, Computer Science, Statistics, or a related field; a Master's degree is preferred.
- Proven experience as a Data Scientist or in a similar analytical role.
- Strong programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy).
- Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib).
- Solid understanding of statistics, probability, and data-driven decision-making.
- Experience working with databases (SQL) and data warehousing solutions.
- Strong problem-solving skills and ability to work collaboratively within a team environment.
- Excellent written and verbal communication skills, with the ability to effectively present complex information.
- Proficiency in English; knowledge of additional languages is a plus.
- Experience in a specific industry sector relevant to the business is desirable.
Data Scientist employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest machine learning frameworks and data visualisation tools mentioned in the job description. Being able to discuss your hands-on experience with tools like Scikit-Learn or Tableau during interviews can set you apart from other candidates.
✨Tip Number 2
Prepare to showcase your analytical skills by working on a personal project or case study that involves complex data analysis. This will not only demonstrate your capabilities but also give you concrete examples to discuss during your interview.
✨Tip Number 3
Network with professionals in the data science field, especially those who work at Keller Executive Search or similar companies. Engaging with them on platforms like LinkedIn can provide insights into the company culture and potentially lead to referrals.
✨Tip Number 4
Stay updated on industry trends and best practices in data science. Being knowledgeable about current developments will not only help you in interviews but also show your commitment to continuous learning, which is highly valued in this role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Scientist role. Emphasise your programming skills in Python or R, and any experience with machine learning frameworks and data visualisation tools.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and how your background makes you a perfect fit for Keller Executive Search. Mention specific projects or experiences that demonstrate your analytical capabilities and problem-solving skills.
Showcase Your Projects: If you have worked on relevant projects, include them in your application. Describe the challenges you faced, the methods you used, and the outcomes. This will help illustrate your practical experience and ability to apply your skills.
Prepare for Technical Questions: Be ready to discuss your technical skills and methodologies during the interview process. Brush up on statistical methods, machine learning algorithms, and data visualisation techniques, as these are crucial for the role.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python or R, and highlight your experience with data manipulation libraries like Pandas and NumPy. You might be asked to solve a coding challenge or explain your approach to a past project, so brush up on your technical knowledge.
✨Demonstrate Your Analytical Thinking
Expect questions that assess your problem-solving abilities. Prepare examples of how you've used statistical methods or machine learning models to tackle complex data challenges. Be ready to explain your thought process and the impact of your analyses on business decisions.
✨Communicate Clearly
Since you'll need to present findings to both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Use visual aids if possible, and be ready to discuss how you would create intuitive dashboards or reports to communicate insights effectively.
✨Stay Updated on Industry Trends
Research current trends in data science and be prepared to discuss how they could apply to the role. Showing that you're proactive about learning and adapting to new technologies will demonstrate your commitment to continuous improvement and innovation in the field.
