Principal Data Scientist

Harnham; Greater London; Hybrid; GBP 125,000; Full time

Job summary

An established industry player is seeking a Principal Data Scientist to spearhead innovative AI solutions. In this pivotal role, you'll leverage your expertise in machine learning to design and productionize models that drive business success. Collaborating with diverse teams, you'll tackle complex challenges in retention, price optimization, and recommendation systems. This hybrid position offers the opportunity to work in a dynamic environment, where your contributions will significantly impact the data and AI landscape. If you're passionate about pushing boundaries and making a tangible difference, this is the role for you.

Qualifications

• Experience in developing machine learning models for various applications.
• Strong knowledge of MLOps and cloud environments.

Responsibilities

• Design and develop machine learning models for AI solutions.
• Collaborate with stakeholders to address business challenges.

Skills

Machine Learning Algorithms

Python

NLP

Computer Vision

MLOps

Statistical Analysis

Education

MSc or PhD in Computer Science

Mathematics or Statistics

Tools

SQL

Spark

Databricks

AWS

Azure

GCP

Job description

This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Harnham

Building Data Science and Machine Learning Teams in the UK | The Talent Driving The Data and AI Revolution

Principal Data Scientist

Up to £125,000

London (Hybrid, 3 days onsite per week)

Company:

A leading marketing and analytics agency is seeking a Lead Data Scientist to develop and deploy end-to-end AI solutions. You'll work on machine learning models for retention, price optimisation, recommendation engines, NLP, and Computer Vision.

Responsibilities:

• Design, develop, and productionize machine learning models across various applications.
• Work with Python (ideally production-level code) and other tools like SQL, Spark, and Databricks.
• Apply clustering, classification, regression, time series modelling, NLP, and deep learning.
• Develop recommendation engines and leverage third-party data enhancements.
• Implement MLOps/DevOps practices in cloud environments (AWS, Azure, GCP).
• Ensure explainability, bias detection, and algorithmic fairness in models.
• Collaborate with stakeholders to translate business challenges into data-driven solutions.

Requirements:

• MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
• Experience in ML algorithms (XGBoost, clustering, regression)
• Expertise in Time Series, NLP, Computer Vision, MLOps
• Knowledge of AWS/Azure/GCP, CI/CD, and Agile development
• Ability to own solutions and manage stakeholders

How to Apply:

Please register your interest by sending your CV to Emily Burgess via the Apply link on this page.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Analyst and Engineering

• Industries

  IT Services and IT Consulting

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