Data & AI Trainer (part-time)

Data & AI Trainer (part-time, freelance)
Company Description: Inspire Careers Finance is part of Inspire Careers, an AI-powered career development and workforce learning platform for individuals and organizations. The platform helps people understand their skills, explore career paths, close capability gaps, and prepare for real employer requirements through AI-driven CV analysis, tailored learning pathways, and skills assessments. For employers, Inspire Careers offers visibility into workforce capabilities, supports targeted learning plans, and aligns teams with emerging business and technology needs. Learning content spans technology, financial markets, and professional development, using practical exercises and assessments to translate training into measurable progress. Built on deep experience in technology recruitment and workforce development, Inspire Careers connects skills development directly to the capabilities employers seek.
You help people in financial services query, move, analyse and govern data, and use AI safely in their jobs. You cover 30 modules, from SQL basics and "AI at Work" for non-technical staff up to Spark, Kafka and MLOps.
Modules you teach
SQL: SQL; SQL Stages 1 to 4 (foundations, joins, window functions, design and performance).
Time-series and market data: kdb+ & q; kdb+/q Stages 1 to 3; Market Data Technology.
Data engineering and messaging: Data Engineering; Apache Hadoop; Apache Spark; Apache Kafka; Snowflake; FIX Protocol; SWIFT Messaging.
Analytics and statistics: Data Science; R; SAS; MATLAB; Business Intelligence & Visualisation.
Governance: Data Governance.
AI: AI & Machine Learning; MLOps; LLM Applications; AI at Work Stages 1 to 4 (understanding AI, using it well, using it safely, AI in your daily role).
What you do in this role
Walk learners through queries and pipelines on trade, price and reference data, live on screen.
Run the AI at Work sessions for people with no technical background, with a firm line on what data never goes into an AI tool.
Review a learner's own SQL, notebook or pipeline and explain how to improve it.
Essential
5+ years working with data in banking, asset management, insurance or fintech.
Strong SQL and Python for data work (pandas), plus hands-on use of at least one of Spark, Kafka, Snowflake or kdb+/q.
Working knowledge of how large language models work, where they fail, and UK data protection duties when using them.
Desirable
kdb+/q in a front-office or market data team.
FIX or SWIFT message handling in production.
R, SAS or MATLAB in a risk, credit or quant team.
A machine learning model taken into production.
Qualifications
Candidates should possess strong skills in Data Analytics and Data Analysis, with experience applying these in practical, workplace or educational settings.
Candidates should possess solid Data Management skills, including handling datasets, ensuring data quality, and working with data pipelines or storage solutions.
Candidates should possess capabilities in Data Modeling, supported by robust Analytical Skills for interpreting results and guiding decision-making.
Relevant experience in teaching, training, or mentoring in data or AI topics, ideally within technology or financial services environments.
Comfort working with modern data and AI tools (e.g., Python, SQL, BI tools, machine learning frameworks) and explaining them to diverse learner groups.
Strong communication and presentation skills, with the ability to simplify complex concepts and engage participants at different skill levels.
Bachelor’s degree or equivalent experience in data science, computer science, statistics, finance, or a related quantitative discipline.
Ability to work on-site in London and collaborate effectively with cross-functional teams focused on learning content and talent development.

Work arrangement
Yes