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Machine Learning & Data Scientist

Experis - ManpowerGroup

Reading

Hybrid

GBP 60,000 - 80,000

Full time

27 days ago

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Job summary

An innovative firm is on the lookout for a Machine Learning & Data Scientist to join their dynamic team. This exciting role focuses on developing AI-powered analytics for autonomous robotic systems, particularly in the renewable energy sector. The successful candidate will work on integrating multimodal machine learning algorithms and predictive models for condition monitoring of high-voltage assets. With a commitment to enhancing global energy transmission, this position offers an opportunity to make a significant impact in a cutting-edge field. If you're passionate about technology and eager to contribute to transformative projects, this role is perfect for you.

Benefits

Share option plan
Flexible hybrid working
Paid vacation time
Contributory Pension
Cycle to work scheme

Qualifications

  • Experience in developing multimodal machine learning models.
  • Familiarity with condition monitoring techniques for high-voltage assets.

Responsibilities

  • Develop and implement machine learning algorithms for multimodal data.
  • Collaborate with teams to integrate AI solutions into robotic systems.

Skills

Machine Learning
Data Science
Python
C++
Problem-solving

Education

Bachelor's degree in Computer Science
Master's degree in Data Science
Bachelor's degree in Electrical Engineering

Tools

Data Visualization Tools

Job description

Job Title: Machine Learning & Data Scientist

Location: Reading, UK (Hybrid)

Salary: Up to £80,000 per annum

About Us: We are dedicated to enhancing the global growth and resilience of renewable energy transmission by delivering intelligent, autonomous robotic monitoring solutions for high-voltage assets. Our mission focuses on supporting power transmission operators worldwide with advanced technologies.

Role Overview: We are seeking a Machine Learning & Data Scientist to join our dynamic team. The ideal candidate will have experience in developing multimodal models and a background in condition monitoring, particularly concerning high-voltage assets. This role offers the opportunity to contribute significantly to the development of AI-powered analytics for autonomous robotic systems.

Key Responsibilities:

  1. Develop and implement machine learning algorithms, focusing on multimodal data integration.
  2. Design and deploy predictive models for condition monitoring of high-voltage assets.
  3. Collaborate with cross-functional teams to integrate AI solutions into autonomous robotic systems.
  4. Analyze large datasets to extract meaningful insights and inform decision-making.
  5. Stay abreast of the latest developments in machine learning and apply them to ongoing projects.

Qualifications:

  1. Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related field.
  2. Proven experience in developing and deploying multimodal machine learning models.
  3. Familiarity with condition monitoring techniques, especially in the context of high-voltage assets.
  4. Proficiency in programming languages such as Python or C++.
  5. Experience with data visualization tools and techniques.
  6. Strong problem-solving skills and the ability to work collaboratively in a team environment.

Desirable Skills:

  1. Experience with autonomous robotic systems.
  2. Knowledge of the energy transmission sector.
  3. Familiarity with ISO 27001 standards.

Benefits:

  1. Share option plan: All full-time employees become eligible for participation in the share option plan after 6 months of employment.
  2. Flexible hybrid working: We allow employees to work in the lab or remote with line-manager approval.
  3. Paid vacation time: We offer twenty-five days paid holiday, and 'unlimited' additional unpaid leave.
  4. Contributory Pension: We provide a workplace pension scheme to help our employees save for their retirement.
  5. Cycle to work scheme: A cycle to work scheme is available for employees.

How to apply?

Please send a CV to danielle.chapman@experis.co.uk

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