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- Tasks: Develop and refine forecasting models to enhance production efficiency.
- Company: Join a global leader in electronics, known for cutting-edge technology and continuous improvement.
- Benefits: Enjoy a competitive salary and opportunities for professional growth in a dynamic environment.
- Why this job: Make a real impact on business decisions while working with innovative technologies and a supportive team.
- Qualifications: Proficiency in Python, SQL, and experience with AWS/SageMaker required; manufacturing background is a plus.
- Other info: Work in an agile setting with minimal supervision, perfect for self-starters.
The predicted salary is between 36000 - 60000 £ per year.
Source Solutions are proud to be working with a successful and continually growing global manufacturer within the electronics space, who operate cutting edge technology within a continuous improvement culture in order to deliver a supreme service to their high profile clients across numerous exciting sectors, in identifying an experienced Data Analyst
This is a key position where your work will have a significant impact on stock and forecasting decisions that will lead to streamlining of production and provide real business and operational value, working on a continual improvement basis.
As you play an active part in embracing data-driven decision-making you will play an exciting role in the design, build and refinement of forecasting models, including time series and machine learning, implementing what-if scenarios for capacity planning and demand variability
Core areas of responsibility;
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Forecasting model development
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Data management
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Model selection and validation
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Model deployment and maintenance
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Proficiency in Python and SQL for data analysis and machine learning.
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Strong experience with AWS / SageMaker or other machine learning platforms.
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Proven ability to work in agile, fast-paced environments with minimal supervision.
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Some experience in manufacturing OR stock and demand forecasting environment
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Familiarity with scenario-based modelling and complex what if analysis.
On offer in return is a competitive salary/package and an opportunity to work with a forward-thinking company working on the cutting edge, who constantly strive toward improvement and excellence in an environment that promotes development of staff.
Data Scientist employer: The Source
Contact Detail:
The Source Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarize yourself with the latest trends in data science, particularly in forecasting models and machine learning. This will not only help you understand the role better but also allow you to engage in meaningful conversations during the interview.
✨Tip Number 2
Showcase your experience with Python and SQL by preparing examples of past projects where you've successfully implemented these tools. Be ready to discuss specific challenges you faced and how you overcame them.
✨Tip Number 3
Highlight any experience you have with AWS or SageMaker, as this is a key requirement for the position. If you have worked on similar platforms, be prepared to explain how you utilized them in your previous roles.
✨Tip Number 4
Demonstrate your ability to work in agile environments by sharing examples of how you've adapted to changes quickly and effectively in past projects. This will show that you can thrive in the fast-paced setting of our company.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data analysis, forecasting models, and proficiency in Python and SQL. Emphasize any relevant projects or roles that demonstrate your ability to work in agile environments.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills in machine learning and data management align with their needs, and provide examples of how you've contributed to data-driven decision-making in previous positions.
Showcase Relevant Experience: When detailing your work history, focus on experiences related to stock and demand forecasting, as well as any familiarity with AWS/SageMaker. Highlight specific achievements that demonstrate your impact on production and operational value.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail, especially regarding forecasting model development and scenario-based modeling. Prepare examples of past projects where you implemented what-if scenarios and how they influenced business decisions.
How to prepare for a job interview at The Source
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and SQL. Bring examples of past projects where you utilized these skills, especially in data analysis and machine learning.
✨Demonstrate Your Experience with Forecasting Models
Highlight your experience in developing forecasting models, particularly time series and machine learning. Be ready to explain your approach to model selection, validation, and deployment.
✨Discuss Your Agile Work Experience
Since the role requires working in fast-paced environments, share specific examples of how you've successfully managed projects with minimal supervision. This will show your adaptability and self-motivation.
✨Prepare for Scenario-Based Questions
Expect questions that involve scenario-based modeling and what-if analyses. Practice articulating your thought process and decision-making strategies in these situations to demonstrate your analytical skills.
