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- Tasks: Deliver innovative data science solutions and build custom forecasting models.
- Company: Join a dynamic consultancy focused on cutting-edge data-driven projects.
- Benefits: Enjoy flexible working options and the chance to work with modern technologies.
- Why this job: Be part of a fast-paced environment that values creativity and adaptability.
- Qualifications: Strong background in data science, machine learning, and web development required.
- Other info: Ideal for those who thrive in agile settings and enjoy tackling diverse challenges.
The predicted salary is between 43200 - 72000 £ per year.
Key Responsibilities:
- Deliver end-to-end data science solutions in a consultancy environment
- Build and deploy custom forecasting models (e.g., time series, XGBoost, deep learning)
- Implement reinforcement learning techniques for dynamic prediction
- Apply causal inference and graph AI methods to uncover complex relationships
- Develop and containerize models using Docker
- Work within modern CI/CD pipelines to streamline deployment
- Operate in a cloud environment (AWS preferred)
- Contribute to the development of a data-driven web application using JavaScript/TypeScript and Next.js
Required Skills & Experience:
- Strong experience as a Full Stack Data Scientist
- Deep expertise in time series forecasting and machine learning (XGBoost, deep learning, reinforcement learning)
- Practical knowledge of Causal AI and Graph AI methodologies
- Proficiency in Python for data science and model development
- Experience with Docker, CI/CD workflows, and AWS
- Comfortable working with JavaScript, Next.js, and ideally TypeScript
- Ability to thrive in a consulting or agency environment with changing client demands
- Strong ownership of delivery and adaptability to fast-moving projects
Desirable:
- Experience in retail analytics
- Prior work in cross-functional teams building web-based data products
- Exposure to start-up style or agile project settings
Contract Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Contract Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in data science, especially in areas like time series forecasting and reinforcement learning. This will not only help you during interviews but also show that you're genuinely interested in the field.
✨Tip Number 2
Build a portfolio showcasing your projects related to machine learning and data science. Include examples of custom forecasting models or any work you've done with Docker and CI/CD pipelines to demonstrate your hands-on experience.
✨Tip Number 3
Network with professionals in the data science community, particularly those who have experience in consultancy environments. Attend meetups or webinars to gain insights and potentially get referrals for the role.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges in Python and brushing up on your knowledge of AWS services. Being able to discuss your approach to deploying models in a cloud environment will set you apart.
We think you need these skills to ace Contract Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Full Stack Data Scientist. Emphasise your expertise in time series forecasting, machine learning techniques like XGBoost and deep learning, and any relevant projects you've completed.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in the Contract Data Scientist role specifically. Mention your experience with causal inference and graph AI methods, and how you can contribute to the development of data-driven web applications.
Showcase Relevant Projects: Include specific examples of projects where you've built and deployed forecasting models or worked with Docker and CI/CD pipelines. This will demonstrate your practical knowledge and ability to deliver end-to-end solutions.
Highlight Adaptability: Since the role requires thriving in a consultancy environment, mention instances where you've successfully adapted to changing client demands or fast-moving projects. This will show that you can handle the dynamic nature of the job.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with time series forecasting, machine learning techniques like XGBoost and deep learning. Bring examples of past projects where you've successfully implemented these skills, as this will demonstrate your expertise.
✨Demonstrate Your Problem-Solving Ability
Consultancy environments often require quick thinking and adaptability. Prepare to discuss how you've tackled complex data problems in the past, particularly using causal inference and graph AI methods. Real-world examples will help illustrate your thought process.
✨Familiarise Yourself with CI/CD and Cloud Environments
Since the role involves working within modern CI/CD pipelines and cloud environments like AWS, make sure you can speak confidently about your experience with Docker and deployment processes. Highlight any relevant projects where you've used these technologies.
✨Prepare for a Collaborative Discussion
Given the emphasis on cross-functional teamwork, be ready to discuss how you've worked with others to build web-based data products. Share experiences that showcase your ability to thrive in agile settings and adapt to changing client demands.
