Negotiable
Undetermined
Remote
United Kingdom
Summary: The Data Science Expert role involves analyzing large datasets to enhance AI model design and performance. The position requires developing statistical models and machine learning techniques while collaborating with research teams in a fully remote environment. The expert will also build tools for data processing and support continuous model improvement initiatives. This role demands strong analytical skills and proficiency in Python and data science libraries.
Key Responsibilities:
- Analyze large datasets to extract insights that inform AI model design and refinement.
- Develop and apply statistical models, machine learning techniques, and evaluation frameworks.
- Conduct performance assessments and data quality reviews on AI model outputs.
- Build reusable tools for data processing, visualization, and reporting.
- Partner with research teams to test hypotheses and scale experimental workflows.
- Support data-driven experimentation and continuous model improvement initiatives.
Key Skills:
- Strong professional background in data science, machine learning, or related analytical fields.
- Proficiency in Python and core data science libraries (e.g., pandas, NumPy, scikit-learn).
- Familiarity with large-scale data environments and version-controlled workflows.
- Strong understanding of statistical analysis, experimental design, and model validation.
- Excellent written communication skills and ability to collaborate across technical teams.
- Ability to work independently in a fully remote environment.
Salary (Rate): £90.00/hr
City: undetermined
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Position: Data Science Expert
Type: Hourly contract
Compensation: $50–$90/hour
Location: Remote
Commitment: 10–40 hours/week
Role Responsibilities
- Analyze large datasets to extract insights that inform AI model design and refinement.
- Develop and apply statistical models, machine learning techniques, and evaluation frameworks.
- Conduct performance assessments and data quality reviews on AI model outputs.
- Build reusable tools for data processing, visualization, and reporting.
- Partner with research teams to test hypotheses and scale experimental workflows.
- Support data-driven experimentation and continuous model improvement initiatives.
Requirements
- Strong professional background in data science, machine learning, or related analytical fields.
- Proficiency in Python and core data science libraries (e.g., pandas, NumPy, scikit-learn).
- Familiarity with large-scale data environments and version-controlled workflows.
- Strong understanding of statistical analysis, experimental design, and model validation.
- Excellent written communication skills and ability to collaborate across technical teams.
- Ability to work independently in a fully remote environment.
Application Process (Takes 20 Mins)
- Upload resume
- Interview (15 min)
- Submit form