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- Tasks: Join an agile data team as a Data Scientist, tackling exciting challenges in a fast-paced environment.
- Company: Work with a well-established client in the pet services and retail sector, based in Doncaster.
- Benefits: Enjoy a hybrid work model with remote options and a pet-friendly office atmosphere.
- Why this job: This role offers hands-on experience in data science while driving positive change and mentoring others.
- Qualifications: A degree in mathematics, statistics, or a related field; expertise in SQL and Python is essential.
- Other info: Interviews are happening next week, so apply now to secure your spot!
The predicted salary is between 60000 - 84000 £ per year.
Data Scientist (Contract) We have a new requirement for a Data Scientist to join an agile data team on an initial 6-month contract. This is for a client based in Doncaster, who are an established company working within the pet services and retail sector. This is a hybrid role with some days onsite at our pet-friendly office in Doncaster and some days working from home. We will consider candidates based elsewhere across the UK depending on experience. Details: Data Scientist 6 months (initial contract) Hybrid Remote (Doncaster) £350/day (Outside IR35) Our Ideal Candidate: Will enjoy working in a fast paced, agile team environment, who can deliver against tight and changing deadlines and priorities. Is passionate about the art of Data Science, has the right attitude for solving problems, “getting stuff done” and is hungry to learn. Will be a motivated, curious, and analytically minded person who enjoys driving positive change using data. Enjoy interacting with colleagues and the hurly-burly of office life. Be able to manage workload and communicate the personal challenges they are facing. Enjoy teaching and mentoring colleagues into the paradise of data wisdom. What skills and experience interest us: Highly numerate with a degree, or equivalent experience, in mathematics, statistics, science or related technical field. Expertise in SQL and Python, with knowledge of ELT/ETL tools and/or Snowflake advantageous. Experience processing large data sets and matching/merging data sets . Demonstrable knowledge of applying statistical methods to data analysis, with experience of developing and deploying ML algorithms advantageous. Knowledge of data mining techniques and where to apply these in a business environment. Strong experience of implementing good software development practices (e.g. Git, ML Ops, Sprint planning etc.) Excellent communication skills, with the ability to translate technical findings to non-technical stakeholders. We’re looking to get interviews booked in next week.. This will be a one stage Teams call with the Head of Data. Please click APPLY or send your CV to , if you are an experienced Data Analyst looking for tier next contract. In Technology Group Ltd is acting as an Employment Business in relation to this vacancy
Data Scientist (Contract) employer: In Technology Group
Contact Detail:
In Technology Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Contract)
✨Tip Number 1
Make sure to showcase your experience with SQL and Python during the interview. Be ready to discuss specific projects where you utilized these skills, as they are crucial for this role.
✨Tip Number 2
Prepare examples of how you've worked in agile teams before. Highlight your ability to adapt to changing priorities and tight deadlines, as this is a key aspect of the job.
✨Tip Number 3
Since communication is vital, think of ways you've successfully translated complex data findings to non-technical stakeholders. This will demonstrate your ability to bridge the gap between technical and non-technical team members.
✨Tip Number 4
Show your passion for data science by discussing any personal projects or continuous learning efforts you've undertaken. This will reflect your motivation and curiosity, which are highly valued in this role.
We think you need these skills to ace Data Scientist (Contract)
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Scientist position. Understand the key responsibilities and required skills, such as expertise in SQL and Python, and be prepared to highlight your relevant experience.
Tailor Your CV: Customize your CV to reflect the skills and experiences that align with the job requirements. Emphasize your analytical mindset, problem-solving abilities, and any experience you have with data mining techniques or machine learning algorithms.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your ability to work in an agile team environment. Mention specific projects or experiences that demonstrate your capability to deliver under tight deadlines.
Prepare for the Interview: Since the interview will be a Teams call with the Head of Data, practice articulating your technical findings in a way that is understandable to non-technical stakeholders. Be ready to discuss your previous work with large data sets and your approach to mentoring colleagues.
How to prepare for a job interview at In Technology Group
✨Show Your Passion for Data Science
Make sure to express your enthusiasm for data science during the interview. Share specific examples of projects you've worked on that demonstrate your problem-solving skills and your eagerness to learn new techniques.
✨Demonstrate Technical Proficiency
Be prepared to discuss your experience with SQL and Python in detail. Highlight any projects where you processed large datasets or applied statistical methods, as this will show your technical expertise and relevance to the role.
✨Communicate Effectively
Since the role requires translating technical findings to non-technical stakeholders, practice explaining complex concepts in simple terms. This will showcase your communication skills and ability to work collaboratively within a team.
✨Prepare for Agile Environment Questions
Expect questions about your experience in agile environments. Be ready to discuss how you manage tight deadlines and changing priorities, and provide examples of how you've successfully adapted to such situations in the past.
