Production ML Data Scientist for EMEIA Sales Finance

Apple; Greater London; On-site; GBP 55,000 - 75,000; Full time

Job summary

A leading technology company in the UK is seeking a Data Scientist to provide data and automation infrastructure for commercial insights. This role requires 5 years of experience in machine learning, strong proficiency in Python and SQL, and the ability to collaborate with cross-functional teams. The successful candidate will drive AIML adoption and focus on areas such as forecasting and data pipeline management, leveraging advanced analytics tools.

Qualifications

• 5 years of hands‑on experience building and deploying machine learning models in a production environment.
• Strong proficiency in Python and its core data science libraries.
• Strong proficiency in SQL with hands‑on experience in modern data platforms.

Responsibilities

• Collaborate with cross-functional teams to solve challenging problems.
• Drive AIML adoption across Sales Finance.
• Focus on forecasting, anomaly detection, and data pipeline management.

Skills

Building and deploying machine learning models

Strong proficiency in Python

Strong proficiency in SQL

Data pipelines development

Experience with MLOps principles and tools

Applying machine learning techniques

Understanding of statistical analysis

Cloud data science platforms experience

Deploying infrastructure on cloud platforms

Software design principles

Full data science project delivery lifecycle

Strong verbal / written communication skills

Detail oriented and self-motivated

Education

BS / MS in Data Science / Machine Learning Mathematics Statistics Information Systems or related field

Tools

Tableau

BusinessObjects

Git

Job description

A leading technology company in the UK is seeking a Data Scientist to provide data and automation infrastructure for commercial insights. This role requires 5 years of experience in machine learning, strong proficiency in Python and SQL, and the ability to collaborate with cross-functional teams. The successful candidate will drive AIML adoption and focus on areas such as forecasting and data pipeline management, leveraging advanced analytics tools.