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Data Scientist

Job in Newcastle upon Tyne, Newcastle, Tyne and Wear, SY7, England, UK
Listing for: Chi Square Economics
Full Time position
Listed on 2026-07-06
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 45000 - 65000 GBP Yearly GBP 45000.00 65000.00 YEAR
Job Description & How to Apply Below
Location: Newcastle upon Tyne

Chi Square Group is currently partnering with a growing consulting firm in the search for a Data Scientist to join its expanding team. This firm delivers cutting-edge consulting and software solutions to organisations across the finance and defence sectors, helping them solve complex challenges through data-driven decision-making and advanced analytics.

This is a unique opportunity to work alongside exceptional researchers, data specialists, and quantitative professionals in a highly intellectual and collaborative environment where data-driven insights directly influence strategic decision-making.

The successful candidate will leverage a wide range of traditional, public, financial, and alternative datasets to uncover valuable signals, develop predictive models, and contribute to high-impact analytical projects. This role offers the opportunity to work at the intersection of data science, machine learning, and real-world decision-making within a fast-paced and innovative setting.

Key Responsibilities
  • Analyse large and complex structured and unstructured datasets to identify meaningful patterns, trends, and opportunities.
  • Develop predictive models and advanced analytical solutions that support critical business and research objectives.
  • Partner closely with stakeholders to understand key challenges and translate data into actionable insights.
  • Design, build, and enhance data products that improve the accessibility and value of analytical outputs.
  • Collaborate with data engineering teams to leverage automated data pipelines and ensure high-quality data delivery.
  • Evaluate and integrate alternative datasets to generate differentiated insights and uncover new opportunities.
  • Apply statistical, machine learning, and artificial intelligence techniques to solve complex analytical problems.
  • Continuously improve analytical processes, methodologies, and tools to increase efficiency and impact.
  • Stay current with developments in data science, machine learning, artificial intelligence, and emerging technologies.
Candidate Requirements
  • Bachelor's, Master's, or PhD in a highly quantitative discipline from a recognised university (Russell Group University / top 300 in the world)
  • Strong programming skills in Python and SQL.
  • Experience using Azure & Databricks is desirable.
  • Experience working with large and complex datasets, including both structured and unstructured data.
  • Solid understanding of statistical modelling, machine learning techniques, and applied data science methodologies.
  • Experience building predictive models and analytical solutions that support business decision‑making.
  • Knowledge of cloud‑based data platforms and modern data science tooling is advantageous.
  • Exposure to financial, economic, or alternative datasets would be beneficial but is not essential.
  • Strong problem‑solving skills with the ability to work independently and take ownership of projects.
  • Excellent communication skills, with the ability to explain complex analytical concepts to both technical and non‑technical audiences.
  • Highly organised, detail‑oriented, and motivated to continuously learn and develop new skills.
  • Ability to thrive in a fast‑paced, collaborative, and intellectually challenging environment.
What's on Offer
  • Competitive compensation package.
  • Opportunity to work alongside exceptional researchers, data scientists, and quantitative specialists.
  • Meaningful ownership and responsibility from day one.
  • Exposure to a diverse range of high‑impact projects spanning data science, analytics, machine learning, and quantitative research.
  • Continuous learning and professional development opportunities.
  • Access to cutting‑edge datasets, technologies, and analytical techniques.
  • Chance to play a key role in shaping a rapidly growing and innovative organisation.
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