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- Tasks: Lead the development of forecasting models for a major media organisation.
- Company: Join a dynamic media company focused on digital performance and innovation.
- Benefits: Enjoy flexible working arrangements and the chance to work with cutting-edge technology.
- Why this job: Make a real impact by predicting ad revenue and website traffic in a collaborative environment.
- Qualifications: Expertise in time series forecasting, strong Python and SQL skills required.
- Other info: Opportunity to work with cloud technologies and enhance your data science portfolio.
The predicted salary is between 43200 - 72000 £ per year.
We're hiring a contract Data Scientist to lead the development of forecasting models for a major media organisation. The project is fully scoped and delivery-focused; you'll be responsible for building daily, weekly, and monthly time series models to predict ad revenue, website traffic, and overall digital performance.
Key Responsibilities- Build and deploy time series forecasting models to predict traffic, ad performance, and revenue
- Work across multiple temporal resolutions (daily, weekly, monthly)
- Collaborate with stakeholders in product, marketing, and commercial teams to define inputs and targets
- Work with structured web analytics and revenue data in a cloud environment
- Ensure models are robust, explainable, and production-ready
- Python (NumPy, Pandas, scikit-learn)
- SQL
- GCP (BigQuery, Cloud Functions)
- Deployment: Docker, Kubernetes, Airflow
- Git, CI/CD pipelines
- Tableau (optional)
- Proven expertise in time series forecasting at multiple projects
- Strong Python and SQL skills
- Experience deploying models into production in a cloud environment (GCP preferred)
- Ability to work independently and manage delivery from end to end
- Strong communication skills for cross-team collaboration
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Time Series Data Scientist (Contract)
✨Tip Number 1
Familiarise yourself with the specific time series forecasting techniques that are relevant to the media industry. Understanding how to apply models like ARIMA or Prophet in a practical context will give you an edge during discussions with our team.
✨Tip Number 2
Brush up on your Python and SQL skills, especially focusing on libraries like NumPy and Pandas. Being able to demonstrate your proficiency in these tools during technical discussions will show us that you're ready to hit the ground running.
✨Tip Number 3
Prepare to discuss your previous experience with deploying models in a cloud environment, particularly GCP. Be ready to share specific examples of how you've managed end-to-end delivery of projects, as this is crucial for the role.
✨Tip Number 4
Since collaboration is key in this role, think about how you can effectively communicate complex data insights to non-technical stakeholders. Practising how to explain your work in simple terms will help you stand out during interviews.
We think you need these skills to ace Time Series Data Scientist (Contract)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with time series forecasting, Python, and SQL. Include specific projects where you've built and deployed models, especially in a cloud environment.
Craft a Compelling Cover Letter: In your cover letter, emphasise your ability to work independently and manage projects from start to finish. Mention your strong communication skills and how they will help you collaborate with various teams.
Showcase Relevant Projects: Include examples of previous projects that demonstrate your expertise in time series forecasting. Be specific about the tools you used, such as NumPy, Pandas, or GCP, and the outcomes of your work.
Proofread Your Application: Before submitting, carefully proofread your application for any errors or typos. A polished application reflects your attention to detail, which is crucial for a Data Scientist role.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and any relevant libraries like NumPy and Pandas. Highlight specific projects where you've built time series forecasting models, and be ready to explain your approach and the outcomes.
✨Understand the Business Context
Research the media organisation and its digital performance metrics. Be ready to discuss how your forecasting models can directly impact ad revenue and website traffic, demonstrating your understanding of the business needs.
✨Prepare for Collaboration Questions
Since the role involves working with various teams, think of examples where you've successfully collaborated with stakeholders. Be ready to discuss how you gather requirements and ensure that your models meet their expectations.
✨Demonstrate Your Problem-Solving Skills
Expect questions about challenges you've faced in previous projects, especially related to model deployment in a cloud environment. Prepare to discuss how you overcame these challenges and ensured your models were robust and production-ready.