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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 work options, competitive pay, and opportunities for professional growth.
- Why this job: Be part of a fast-paced environment where your skills can make a real impact.
- Qualifications: Strong background in data science, machine learning, and proficiency in Python required.
- Other info: Experience in retail analytics and agile settings is a plus.
The predicted salary is between 36000 - 60000 £ 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
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 positions like the one we have at StudySmarter.
✨Tip Number 4
Prepare to discuss how you've adapted to changing client demands in previous roles. Highlight specific examples where you've successfully navigated fast-moving projects, as this is crucial for a role in a consultancy setting.
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 position. Mention specific skills that align with the job description, such as your experience with Docker, CI/CD workflows, and cloud environments like AWS.
Showcase Relevant Projects: Include examples of past projects where you delivered data science solutions, particularly those involving causal inference, graph AI methods, or web applications using JavaScript/TypeScript and Next.js. This will demonstrate your practical knowledge and problem-solving abilities.
Highlight Adaptability: Since the role requires thriving in a consulting environment, mention instances where you've successfully adapted to changing client demands or worked in fast-paced project settings. This will show your potential employer 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, XGBoost, and deep learning. Bring examples of past projects where you've successfully implemented these techniques, as this will demonstrate your expertise and problem-solving abilities.
✨Demonstrate Your Consultancy Experience
Since the role involves working in a consultancy environment, share specific instances where you've adapted to changing client demands. Highlight your ability to communicate complex data science concepts to non-technical stakeholders.
✨Familiarise Yourself with Docker and CI/CD
Make sure you understand how to develop and containerise models using Docker, as well as how to work within CI/CD pipelines. Be ready to discuss any relevant experiences or challenges you've faced in these areas.
✨Prepare for Behavioural Questions
Expect questions about your adaptability and ownership of delivery. Think of examples that showcase your ability to thrive in fast-paced environments and how you've contributed to cross-functional teams in previous roles.
