Job Description

We are looking for a

Junior Data Scientist

to join our team and contribute to the development of

machine learning models for failure detection and prediction in industrial equipment

. This is an excellent opportunity for someone with a strong analytical background and a passion for real-world applications of AI in the industrial sector. The role is ideal for a recent graduate or early-career professional who wants to grow in the field of applied data science and machine learning.

Key Responsibilities

Build, validate, and monitor machine learning models to

detect anomalies

and

predict failures

in industrial machinery. Support the implementation of

predictive maintenance strategies

by analyzing sensor data and operational logs. Develop and maintain

data pipelines

using tools such as

Apache Airflow

to ensure efficient and reproducible workflows. Use

MLflow

for experiment tracking, model versioning, and deployment management. Participate in model evaluation, data cleaning, and feature engineering processes. Work collaboratively with engineers and data teams to understand equipment behavior and improve model accuracy.

Required Qualifications

Bachelor's degree in

Electrical Engineering, Mathematics, Computer Science

, or a related quantitative field. Experience with

Python

for data analysis and modeling (e.g., Pandas, Scikit-learn). Strong understanding of machine learning concepts and algorithms. Interest in working with

real-world industrial data

(sensor data, telemetry, maintenance logs). Experience or coursework using

Apache Airflow

and/or

MLflow

is a strong plus. Strong problem-solving attitude and willingness to learn in a collaborative environment.
Job Type: Fixed term contract
Contract length: 12 months

Pay: 30,000.00-50,000.00 per year

Benefits:

Flexitime Work from home
Education:

Bachelor's (required)
Experience:

work with real industrial data: 1 year (required)
Work authorisation:

United Kingdom (required)
Work Location: Hybrid remote in London W1J