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- Tasks: Deliver innovative data science solutions and build custom forecasting models.
- Company: Join a dynamic consultancy that thrives on cutting-edge technology and data-driven insights.
- Benefits: Enjoy flexible working options, competitive pay, and opportunities for professional growth.
- Why this job: Be part of a collaborative culture where your skills can make a real impact in diverse projects.
- Qualifications: Strong background in data science, machine learning, and proficiency in Python and JavaScript required.
- Other info: Ideal for those who thrive in fast-paced environments and enjoy tackling complex 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
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. Highlight any custom forecasting models or web applications you've developed, as this will demonstrate your practical skills and experience.
✨Tip Number 3
Network with professionals in the data science community, particularly those who work in consultancy environments. Attend meetups or webinars to connect with others and gain insights into what companies like us are looking for in candidates.
✨Tip Number 4
Prepare to discuss how you've adapted to changing client demands in previous roles. Being able to showcase your adaptability and ownership of delivery will resonate well with our team, especially in a fast-paced consulting environment.
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 worked on.
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 end-to-end data science solutions. Highlight your work with causal inference, graph AI methods, and any contributions to web applications using JavaScript or TypeScript.
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 demonstrate your ability to 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 Docker and CI/CD
Since the role involves developing and containerising models, make sure you can talk about your experience with Docker and CI/CD pipelines. Be ready to explain how you've used these tools to streamline deployment in previous projects.
✨Understand the Consulting Environment
As the role requires thriving in a consultancy setting, be prepared to discuss how you've managed changing client demands and worked within cross-functional teams. Highlight your adaptability and ownership of project delivery to show you're a good fit for this dynamic environment.
