Data Scientist - Time Series Forecasting

ZipRecruiter; London; Hybrid; GBP 150,000 - 200,000; Full time

Job summary

A leading company in the media sector is seeking a contract Data Scientist to develop and deploy time series forecasting models. This role is pivotal to predict ad revenue and website traffic. You will work in a hybrid setting, utilizing Python and SQL within a cloud environment to ensure robust and explainable models. The position is focused on cross-team collaboration and independent delivery management over a 6-month duration with competitive daily rates.

Qualifications

• Proven expertise in time series forecasting at multiple granularities.
• Strong Python and SQL skills essential.
• Experience deploying models into production in a cloud environment (GCP).

Responsibilities

• Build and deploy time series forecasting models to predict traffic, ad performance, and revenue.
• Collaborate with stakeholders in product, marketing, and commercial teams to define inputs and targets.

Skills

time series forecasting

Python

SQL

cloud deployment

stakeholder collaboration

Tools

NumPy

Pandas

scikit-learn

GCP

Docker

Kubernetes

Airflow

Git

CI/CD pipelines

Tableau

Job description

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 )

• 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