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Data Scientist

Job in Paisley, Renfrewshire, PA1, Scotland, UK
Listing for: Jobgether
Full Time position
Listed on 2026-07-07
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software)
Job Description & How to Apply Below

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist based in United Kingdom. This is an opportunity to join a fast-paced, product-driven environment where data science directly shapes user experience and business performance  a Data Scientist, you will design and deploy machine learning systems that power personalization, search, and recommendation features used by a global user base.

The role combines advanced statistical modeling, Python-based development, and cloud technologies to solve high-impact, real-world problems. You will work closely with product and engineering teams to translate complex data into actionable insights and production-ready solutions. The environment is highly collaborative, remote-first, and focused on measurable outcomes. This position is ideal for someone who enjoys owning end-to-end ML systems and seeing their work directly influence business growth.

Accountabilities
  • Develop, implement, and product ionize machine learning models that improve personalization, search ranking, and recommendation systems.
  • Design and build data-driven algorithms that enhance user experience and drive measurable improvements in engagement and conversion rates.
  • Apply advanced statistical methods and data mining techniques to extract insights from large-scale datasets.
  • Collaborate with engineering and product teams to integrate ML models into production systems and ensure scalability and reliability.
  • Continuously monitor model performance and iterate based on real-world data and business feedback.
  • Translate business problems into analytical and machine learning solutions with clear impact on key performance indicators.
  • Work with cloud infrastructure and data pipelines to support scalable ML workflows.
  • Contribute to experimentation and A/B testing frameworks to validate model effectiveness.
Requirements
  • Minimum of 2 years of experience as a Data Scientist, Quantitative Analyst, Quantitative Researcher, or similar analytical role.
  • Strong proficiency in Python and its data science ecosystem (e.g., pandas, Num Py, scikit-learn or similar tools).
  • Solid foundation in probability, statistics, machine learning, and linear algebra.
  • Proven experience applying ML models to real-world business problems with measurable impact on revenue or key metrics.
  • Good knowledge of SQL and experience working with relational databases.
  • Experience working with cloud platforms such as AWS, GCP, or Microsoft Azure is highly desirable.
  • Familiarity with product ionizing ML models and working in end-to-end data science pipelines.
  • Comfortable working in a fast-paced, product-oriented environment with cross-functional stakeholders.
  • Strong communication skills and ability to explain technical concepts to non-technical audiences.
  • Bachelor’s or Master’s degree in Applied Mathematics, Computer Science, Engineering, Financial Engineering, or a related quantitative field.
  • Experience using AI tools or agents as part of the development workflow is considered an advantage.
  • Knowledge of Apache Spark and/or experience in the gaming industry is a plus.
Benefits
  • Fully remote-first organization with flexible working arrangements.
  • Competitive salary with quarterly performance-based bonuses.
  • 28 days of paid annual leave.
  • Flexible working hours with core availability between 10am and 3pm local time.
  • Provision of high-end equipment to support your work.
  • Annual company retreats for collaboration and team networking.
  • Referral and performance-based bonus programs.
  • Opportunity to work on large-scale machine learning systems with direct business impact.
  • Strong emphasis on professional growth and exposure to modern ML and cloud technologies.
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