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- Tasks: Lead the development of time series forecasting models for ad revenue and digital performance.
- Company: Join a leading digital media organisation focused on data-driven growth.
- Benefits: Enjoy hybrid working, competitive pay, and a modern tech stack.
- Why this job: Make a measurable impact from day one in a dynamic environment.
- Qualifications: 5+ years in time series forecasting, strong Python and SQL skills required.
- Other info: 6-month contract with potential for extension; work with cross-functional teams.
This is an exciting opportunity for a Data Scientist to lead the development of robust time series forecasting models for a major media organisation. You'll take ownership of a fully scoped, delivery-focused project, working across daily, weekly, and monthly resolutions to forecast ad revenue, website traffic, and digital performance. The environment offers autonomy, technical depth, and the chance to make a measurable business impact from day one.
A leading name in the digital media space, this organisation is focused on leveraging data to drive growth and performance across its digital channels. With a modern cloud-based tech stack and a growing demand for predictive insights, they’re investing in scalable data science capabilities. Based in London, the team operates on a hybrid model with 2 days a week in their office.
As the lead Data Scientist on this project, you’ll be responsible for the end-to-end delivery of forecasting solutions, from model design to deployment. You’ll collaborate closely with stakeholders across marketing, commercial, and product teams to shape model inputs and outputs that are both business-relevant and technically sound. Your responsibilities will include:
- Building and deploying time series models for revenue, traffic, and ad performance
- Operating across multiple temporal resolutions (daily, weekly, monthly)
- Working with structured web analytics and revenue data in a cloud environment
- Ensuring models are robust, explainable, and scalable for production use
- Collaborating with cross-functional teams to understand needs and define targets
- Managing delivery independently within a scoped project timeline
KEY SKILLS AND REQUIREMENTS
- 5+ years' experience delivering commercial time series forecasting projects
- Strong programming ability in Python (NumPy, Pandas, scikit-learn)
- Solid SQL skills and experience working with large datasets
- Experience deploying models into production environments (GCP preferred)
- Strong communication skills and stakeholder collaboration experience
- Ability to manage the full delivery lifecycle autonomously
TECH STACK
- Python, SQL
- GCP (BigQuery, Cloud Functions)
- Docker, Kubernetes, Airflow
- Git, CI/CD pipelines
- Tableau (optional)
WHY APPLY
- Lead a high-impact forecasting project for a major media brand
- Work with a modern, cloud-first tech stack
- Hybrid working: £600/day (Inside IR35, up to £650 billing rate)
- 6-month initial contract
HOW TO APPLY
Please register your interest by sending your CV via the apply link on this page.
Data Scientist - Time Series Forecasting employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Time Series Forecasting
✨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 commercial context can set you apart during discussions.
✨Tip Number 2
Brush up on your Python skills, especially with libraries like NumPy and Pandas. Being able to demonstrate your coding proficiency in these areas during technical discussions will show that you're ready to hit the ground running.
✨Tip Number 3
Prepare to discuss your experience with deploying models into production environments, particularly using GCP. Having concrete examples of past projects where you've successfully managed this process will be crucial.
✨Tip Number 4
Highlight your ability to collaborate with cross-functional teams. Be ready to share examples of how you've worked with stakeholders from different departments to ensure that your models meet business needs effectively.
We think you need these skills to ace Data Scientist - Time Series Forecasting
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with time series forecasting and relevant programming skills, particularly in Python and SQL. Use specific examples from your past projects that demonstrate your ability to deliver robust models.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their needs, especially your experience in deploying models into production environments and collaborating with cross-functional teams.
Showcase Technical Skills: Clearly outline your technical skills related to the job description. Mention your proficiency in tools like GCP, Docker, and CI/CD pipelines, and provide examples of how you've used these technologies in previous roles.
Highlight Communication Abilities: Since the role involves collaboration with various stakeholders, emphasise your strong communication skills. Provide examples of how you've successfully worked with different teams to achieve project goals.
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 successfully built and deployed time series forecasting models.
✨Understand the Business Context
Research the media organisation and its digital channels. Be ready to explain how your forecasting models can directly impact their ad revenue and website traffic, demonstrating your understanding of their business needs.
✨Prepare for Stakeholder Collaboration
Since the role involves working closely with various teams, think of examples where you've effectively communicated complex data insights to non-technical stakeholders. This will show your ability to bridge the gap between technical and business perspectives.
✨Demonstrate Autonomy in Project Management
Discuss your experience managing the full delivery lifecycle of projects independently. Provide examples of how you've met deadlines and delivered results, as this role requires a high level of autonomy.
