Hybrid Data Science & Analytics Consultant

Hybrid Data Science & Analytics Consultant

Full-Time 50000 - 60000 Β£ / year (est.) No working from home possible
Eworker

At a Glance

  • Tasks: Apply data science and ML to solve real client challenges and make data-driven decisions.
  • Company: Join PA Consulting, a leader in digital and data solutions.
  • Benefits: Enjoy hybrid work, a learning budget, and opportunities for professional growth.
  • Other info: Collaborative environment with agile projects and diverse teams.
  • Why this job: Make a real impact by translating complex data into actionable insights across various sectors.
  • Qualifications: Experience in data science and strong analytical skills required.

The predicted salary is between 50000 - 60000 Β£ per year.

PA Consulting in the UK is seeking an experienced Data Science consultant to join our Digital & Data team.

You will apply mathematical modelling and ML to real client challenges, translating complex data into actionable decisions.

You will work across sectors, collaborate with product, design and engineering colleagues, and contribute to agile projects.

The role supports hybrid work with client sites and office days, plus a learning budget and professional growth opportunities.

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Hybrid Data Science & Analytics Consultant employer: Eworker

At Safran, we pride ourselves on being an exceptional employer, offering a dynamic work environment in Cwmbran, South Wales, where innovation and collaboration thrive. Our commitment to employee growth is evident through extensive training opportunities, a supportive culture that values diversity, and a comprehensive benefits package including generous holiday allowances and private medical cover. Join us in crafting excellence together as we lead the way in aerospace technology and create a sustainable future for all.

Eworker

Contact Details:

Eworker Recruitment Team

We think you need these skills to ace Hybrid Data Science & Analytics Consultant

Communication Skills
Python
Problem-Solving Skills
SQL
Attention to Detail
Automation
Data Engineering