Data Scientist - Time Series Forecasting

JR United Kingdom; Slough; Hybrid; GBP 125,000 - 150,000; Full time

Job summary

A leading company in the media sector is seeking a Contract Data Scientist to develop and implement forecasting models for predicting ad revenue and website traffic. This 6-month hybrid role requires strong Python and SQL skills, with a focus on collaboration with cross-functional teams to ensure delivery of robust and explainable models.

Qualifications

• Proven expertise in time series forecasting at multiple granularities.
• Experience deploying models into production in a cloud environment (GCP preferred).
• Strong communication skills for cross-team collaboration.

Responsibilities

• Build and deploy time series forecasting models to predict traffic, ad performance, and revenue.
• Collaborate with stakeholders in product, marketing, and commercial teams.
• Work with structured web analytics and revenue data in a cloud environment.

Skills

Time series forecasting

Python

SQL

Communication

Tools

NumPy

Pandas

scikit-learn

GCP

Docker

Kubernetes

Airflow

Git

Tableau

Job description

Contract Data Scientist - Time Series Forecasting

Duration: 6 months

Rate: £600-700/day (Inside IR35)

Location: Hybrid - 1-2 days/week in Central London

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

Tech Environment

• Python (NumPy, Pandas, scikit-learn)
• SQL
• GCP (BigQuery, Cloud Functions)
• Deployment: Docker, Kubernetes, Airflow
• Git, CI/CD pipelines
• Tableau (optional)

Requirements

• Proven expertise in time series forecasting at multiple granularities
• 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

Desired Skills and Experience

Time series forecasting, temporal modelling, Python, SQL, scikit-learn, Pandas, NumPy, Prophet, GCP, cloud deployment, productionising models, data pipelines, model validation, stakeholder collaboration, media data