Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Analyze data to find patterns and build predictive models.
- Company: Join a forward-thinking company focused on leveraging data for better decisions.
- Benefits: Enjoy a collaborative environment with opportunities for growth and learning.
- Why this job: Make an impact by turning raw data into valuable insights and solutions.
- Qualifications: BSc/BA in relevant field; experience in data science or analysis is a plus.
- Other info: Passion for machine learning and strong analytical skills are essential.
The predicted salary is between 43200 - 72000 £ per year.
We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions.
Data Scientist responsibilities include:
Undertaking data collection, preprocessing and analysis
Building models to address business problems
Presenting information using data visualization techniques
Job brief
We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions.
Responsibilities
Identify valuable data sources and automate collection processes
Undertake to preprocess of structured and unstructured data
Analyze large amounts of information to discover trends and patterns
Build predictive models and machine-learning algorithms
Combine models through ensemble modeling
Present information using data visualization techniques
Propose solutions and strategies to business challenges
Collaborate with engineering and product development teams
Proven experience as a Data Scientist or Data Analyst
Experience in data mining
Understanding of machine-learning and operations research
Knowledge of R, SQL, and Python; familiarity with Scala, Java or C++ is an asset
Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
Analytical mind and business acumen
Strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills
BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
Data Scientist[London, UK] employer: FallenAmbers
Contact Detail:
FallenAmbers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist[London, UK]
✨Tip Number 1
Familiarize yourself with the specific data tools and programming languages mentioned in the job description, such as R, SQL, and Python. Having hands-on experience with these technologies will not only boost your confidence but also demonstrate your readiness for the role.
✨Tip Number 2
Showcase your analytical skills by preparing a portfolio of projects that highlight your ability to analyze data and build predictive models. This can include case studies or personal projects that illustrate your problem-solving capabilities and passion for machine learning.
✨Tip Number 3
Network with current Data Scientists or professionals in the field through platforms like LinkedIn. Engaging in conversations about industry trends and challenges can provide you with valuable insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your thought process during data analysis and model building in interviews. Being able to articulate your approach to problem-solving and critical thinking will set you apart from other candidates.
We think you need these skills to ace Data Scientist[London, UK]
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, machine learning, and programming languages like R, SQL, and Python. Use specific examples to demonstrate your analytical skills and problem-solving abilities.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how it aligns with the company's goals. Mention any specific projects or experiences that showcase your ability to analyze trends and build predictive models.
Showcase Your Technical Skills: Include a section in your application that lists your technical skills, such as familiarity with business intelligence tools like Tableau and data frameworks like Hadoop. This will help the company see your qualifications at a glance.
Prepare for Data-Driven Questions: Anticipate questions related to data analysis and machine learning during the interview process. Be ready to discuss your approach to solving business problems using data and provide examples of past successes.
How to prepare for a job interview at FallenAmbers
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples of how you've used your analytical skills in past projects. Highlight any experience with data collection, preprocessing, and analysis, as these are crucial for the role.
✨Demonstrate Your Passion for Machine Learning
Share your experiences with machine learning projects or research. Discuss any algorithms you’ve implemented and the outcomes, as this will show your enthusiasm and expertise in the field.
✨Prepare for Technical Questions
Expect questions related to R, SQL, Python, and possibly other programming languages. Brush up on your knowledge of data mining techniques and be ready to solve problems on the spot.
✨Communicate Clearly and Effectively
Since excellent communication skills are essential, practice explaining complex data concepts in simple terms. Be ready to present your findings using data visualization techniques, as this is a key responsibility of the role.
