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For Companies At a Glance
- Tasks: Dive into data, build models, and collaborate with teams to drive insights.
- Company: Join a leading tech company at the forefront of data science innovation.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for growth.
- Why this job: Be part of a dynamic team that values creativity and impact in AI development.
- Qualifications: Graduate degree in a quantitative field and some industry experience required.
- Other info: Ideal for those passionate about learning and solving real-world problems.
The predicted salary is between 28800 - 42000 £ per year.
Basic Qualifications
- Educational Background: Possess a graduate degree in Data Science, Computer Science, Business Analytics, Statistics, Economics, Applied Mathematics, or a related quantitative field from a prestigious institution.
- Professional Experience: Minimum of six months of industry or internship experience in a data science or machine learning engineering role, demonstrating strong proficiency in Python, SQL, and version control using Git.
- Technical Skills: Tried ability to independently fit, evaluate, and interpret statistical and machine learning models within a business context.
- Communication Skills: Excellent verbal and written communication skills, crucial for documenting findings and fostering effective daily collaborations.
- Project Management: Ability to prioritize and meet deadlines in a dynamic environment.
- Attention to Detail: Prodigious attention to detail, ensuring precision in data analysis, model development, and reporting.
Additional Qualifications
- Data orchestration tools such as Airflow.
- Data warehousing solutions like Snowflake.
- Cloud services, including Amazon Web Services (AWS) and Google Cloud Platform.
- Development environments like Visual Studio Code.
- Programming skills in HTML, C, or Java.
- Web application development.
- Data pipeline ingestion processes.
- A high degree of curiosity and motivation to learn new technologies and methodologies.
- Stellar problem-solving skills and logical thinking.
- A strong interest in AI and enthusiasm for AI product development.
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Data Scientist employer: Dice
Contact Detail:
Dice Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your hands-on experience with Python and SQL during networking events or informal meetups. Engaging in discussions about your projects can help you stand out and demonstrate your technical skills.
✨Tip Number 2
Familiarize yourself with data orchestration tools like Airflow and cloud services such as AWS or Google Cloud Platform. Being able to discuss these technologies confidently can give you an edge in interviews.
✨Tip Number 3
Join online communities or forums related to data science and machine learning. Engaging with others in the field can provide valuable insights and potentially lead to job referrals.
✨Tip Number 4
Prepare to discuss your problem-solving approach and how you've applied it in past projects. Employers appreciate candidates who can articulate their thought process and demonstrate logical thinking.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Highlight Your Educational Background: Make sure to clearly state your graduate degree in Data Science or a related field. Mention the prestigious institution you attended, as this is a key requirement.
Showcase Relevant Experience: Detail your industry or internship experience in data science or machine learning. Emphasize your proficiency in Python, SQL, and Git, and provide specific examples of projects you've worked on.
Demonstrate Technical Skills: Include examples of how you've independently fitted, evaluated, and interpreted statistical and machine learning models. Highlight any experience with data orchestration tools, cloud services, or programming languages mentioned in the job description.
Communicate Effectively: Since excellent communication skills are crucial, ensure your application is well-written and free of errors. Use clear language to document your findings and describe your collaborative experiences.
How to prepare for a job interview at Dice
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and Git. Bring examples of projects where you applied these skills, especially in data science or machine learning contexts.
✨Communicate Clearly
Since excellent communication skills are crucial, practice explaining complex concepts in simple terms. Be ready to document your findings clearly and concisely during the interview.
✨Demonstrate Problem-Solving Abilities
Prepare to tackle hypothetical scenarios or case studies that test your analytical thinking and problem-solving skills. Show how you approach challenges logically and creatively.
✨Express Your Curiosity
Highlight your eagerness to learn new technologies and methodologies. Discuss any recent trends in AI or data science that excite you, showing your passion for the field.
