Data Scientist - Remote

YO IT Consulting

London, UKremote countryPosted Jul 14, 2026
Posting intelligenceActively listed

Skills

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About the role

Job Title: Data Scientist

Job Type: Contractor

Location: Remote

Job Summary

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities

Collect, clean, and preprocess diverse data sets to ensure integrity and readiness for analysis.

Develop, validate, and implement statistical models to extract actionable insights from complex data.

Conduct exploratory data analysis to identify trends, patterns, and opportunities for business improvement.

Present findings and recommendations through compelling data visualizations and reports, tailored for technical and non-technical stakeholders.

Collaborate closely with team members to design and execute end-to-end data projects, from ideation to delivery.

Continuously improve analytical methodologies and automation processes to enhance data workflows.

Communicate effectively in both written and verbal formats, ensuring clarity and impact of data-driven recommendations.

Required Skills And Qualifications

Expertise in statistics, mathematics, and data analysis techniques.

Proven experience in collecting, handling, and cleaning large, complex data sets.

Proficiency in programming languages such as Python, R, or similar for data manipulation and modeling.

Strong data modeling skills with experience in building and validating predictive models.

Advanced ability to visualize data using tools like Tableau, Power BI, or related libraries.

Meticulous attention to detail and commitment to data quality at every stage.

Excellent written and verbal communication skills, with an emphasis on clarity and precision.

Preferred Qualifications

Experience working in a remote, cross-functional, or customer-focused team environment.

Background in developing and deploying machine learning solutions in production settings.

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