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- Tasks: Dive deep into data science projects and solve real-world problems at scale.
- Company: Join a dynamic team in a leading tech environment with hybrid work options.
- Benefits: Competitive daily rate, flexible working, and opportunities for professional growth.
- Why this job: Make an impact in supply chain and logistics with your data expertise.
- Qualifications: Experience in applied data science, forecasting, and optimisation is essential.
- Other info: Collaborative culture with a focus on practical solutions and innovation.
Urgent requirement for 7 Senior Data Scientists - Start ASAP! 12 month rolling contracts. Inside IR35. £600-£700 per day. UK, hybrid London (1 day office per week).
I need people who have worked on production ready applied data science products; we are not interested in research heavy backgrounds for this project. Any forecasting or optimization experience is great, particularly in Supply Chain or Logistics domains.
You’ll be comfortable with ambiguity and will want to dive deep and fix problems at scale.
The environment looks a bit like this:
- Python (pandas, numpy, scipy, PySpark)
- SQL
- AWS or GCP (BigQuery / RedShift / Snowflake)
- Spark / Databricks
- Airflow / Dagster
Senior Data Scientist employer: Arrows
Contact Detail:
Arrows Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who have experience in production-ready projects. A friendly chat can lead to insider info about job openings that might not even be advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your applied data science projects, particularly those involving forecasting or optimisation. This will help you stand out and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python, SQL, and cloud platforms like AWS or GCP. Practising common data science interview questions can also give you an edge.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, applying directly can sometimes get you noticed faster than through other channels.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with production-ready data science products. We want to see your hands-on skills, especially in forecasting and optimisation within Supply Chain or Logistics.
Showcase Relevant Projects: Include specific examples of projects where you've tackled ambiguity and solved problems at scale. This will help us understand how you approach challenges and your ability to deliver results.
Highlight Technical Skills: Don’t forget to list your technical skills! Mention your proficiency in Python, SQL, and any cloud platforms like AWS or GCP. We’re keen on seeing your experience with tools like Spark, Databricks, and Airflow.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on this exciting opportunity!
How to prepare for a job interview at Arrows
✨Know Your Tech Stack
Make sure you’re well-versed in the tools mentioned in the job description, like Python, SQL, and AWS or GCP. Brush up on your experience with libraries like pandas and PySpark, as well as data orchestration tools like Airflow. Being able to discuss specific projects where you've used these technologies will really impress.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems in data science, especially in supply chain or logistics. Think about times when you had to deal with ambiguity and how you approached those challenges. This will demonstrate your ability to dive deep and fix problems at scale, which is crucial for this role.
✨Understand the Business Context
Familiarise yourself with the business side of data science. Be ready to discuss how your work can impact the bottom line, particularly in forecasting and optimisation. Showing that you understand the practical applications of your skills will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team, the projects you'll be working on, and the company’s goals. This not only shows your interest but also helps you gauge if the role is the right fit for you. Questions about their current data challenges or how they measure success can lead to a great conversation.
