Applied Statistics & Experimentation Trainer

Bloomberg; Greater London; On-site; GBP 50,000 - GBP 70,000; Full time

Job summary

A leading financial data provider in the UK is seeking a Data Training Specialist to design and deliver training on data analytics and experimental design. This role involves collaborating across teams to develop training materials, conduct hands-on labs and maintain the highest standards for data quality. The ideal candidate will have significant experience in data analytics, proficiency in Python or R, and a strong ability to convey complex concepts to diverse audiences. A passion for continuous learning and engagement with professional communities is essential.

Benefits

Continuous learning opportunities

Collaborative team culture

Qualifications

• 3+ years experience in data analytics or statistics.
• Strong foundation in experimental design and statistical inference.
• Ability to communicate complex topics to varied audiences.

Responsibilities

• Design and deliver training on applied experimentation.
• Build a curriculum on A/B testing and hypothesis testing.
• Create hands-on labs for real dataset experimentation.

Skills

Data analytics

Experimental design

Statistical analysis in Python or R

Project management

Communication

Mentoring or teaching

Problem-solving

Education

Bachelor's degree in Computer Science, Engineering, Data Science or related field

Tools

Python

R

SQL

Pandas

Airflow

Spark

Job description

A leading financial data provider in the UK is seeking a Data Training Specialist to design and deliver training on data analytics and experimental design. This role involves collaborating across teams to develop training materials, conduct hands-on labs and maintain the highest standards for data quality. The ideal candidate will have significant experience in data analytics, proficiency in Python or R, and a strong ability to convey complex concepts to diverse audiences. A passion for continuous learning and engagement with professional communities is essential.