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Senior Data Scientist

Harnham - Data & Analytics Recruitment
Posted 11 hours ago, valid for 15 days
Location

Manchester, Greater Manchester M17 1DJ, England

Contract type

Full Time

Paid Time Off

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

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  • The Senior Data Scientist position is remote-first and based in the UK, offering a salary of £70,000.
  • The role involves designing and deploying high-frequency demand forecasting models to support pricing decisions within a Series D tech scale-up focused on the travel and hospitality industries.
  • Candidates should have a strong background in statistics, machine learning, and time series forecasting, with experience in modern ML models and production-level Python coding.
  • The position requires collaboration across teams and the ability to take ownership of projects, with a focus on innovation and improving model performance.
  • Applicants are encouraged to apply by sending their CV to Daniel Abbasi, with the company providing excellent benefits and equity in a high-growth AI firm.
Senior Data Scientist

Location: Remote-first (UK-based)Salary: £70,000

The Company

A Series D tech scale-up is reshaping the travel and hospitality industries through advanced machine learning and forecasting. Purpose-built for this space, their platform leverages deep learning to drive revenue optimisation, automation, and real-time analytics. With a growing client base of major global travel brands, they're hiring exceptional talent to push the boundaries of what's possible in commercial strategy.

The Role

As a Senior Data Scientist within the Forecasting Algorithms team, you'll design and deploy high-frequency demand forecasting models that directly support pricing decisions. You'll own the full development lifecycle-from modelling to deployment-while collaborating closely with science, product, and engineering stakeholders.

This is a hands-on role suited to someone who thrives on building, testing, and deploying complex statistical models in a production environment. You'll work in a modern MLOps setup, contributing to libraries and frameworks used across the company's data science organisation.

Key Responsibilities:
  • Design and deploy time series forecasting models with a strong focus on accuracy and scalability

  • Improve existing model performance and drive innovation through new methodologies

  • Develop internal ML and forecasting libraries using Python

  • Translate product goals into technical solutions in collaboration with leadership

  • Implement validation frameworks, unit tests, and monitoring pipelines

  • Stay current with advances in machine learning and apply them where appropriate

Tech Stack:
  • Python (Pandas, Polars, SciPy, Scikit-learn, NumPy)

  • Dagster, Argo, GCP

  • Kibana, Elastic

  • DevOps-first approach for model deployment

Skills & Experience:

Essential:

  • Strong background in statistics, machine learning, and time series forecasting

  • Experience with modern ML models (e.g. transformers, CNNs, attention mechanisms)

  • Proficiency in writing production-level Python code

  • Familiarity with CI/CD practices, testing, and model validation

  • Confident working across teams and taking ownership of delivery

  • Strong communication and problem-solving skills

Desirable:

  • Experience in demand forecasting or operations research

  • Familiarity with Bayesian methods, Monte Carlo simulations, or reinforcement learning

  • Exposure to high-scale SaaS or B2C products

Why Apply?
  • Build forecasting systems powering global commercial strategies

  • Collaborate with a world-class data science team

  • Up to £70,000 + equity in a high-growth AI company

  • Excellent benefits: private healthcare, mental health support, nursery benefit (UK), and generous PTO

How to Apply

To apply, please send your CV to Daniel Abbasi via the Apply link on this page.

Apply now in a few quick clicks

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.