PW Is Looking for Data Analytics & GenAI Mentors: Here’s What the Role Involves

Data Analytics and Generative AI require more than theoretical knowledge. Professionals need to work with data tools, programming, visualisation and AI technologies while also being able to explain concepts and guide others through practical problems. PW’s Data Analytics & Generative AI Mentor role brings these skills together, with a focus on hands-on learning, project guidance and feedback.

PW Data Analytics & GenAI Mentor Job 2026

What Will You Do as a Data Analytics & GenAI Mentor at PW?

The role combines technical expertise with hands-on mentoring and project guidance.

Key responsibilities include:

• Conduct hands-on mentoring sessions focused on practical data analytics and Generative AI applications

• Guide learners through real-world data projects

• Help students work through data ingestion, preparation, analysis and presentation

• Review student code, analytical approaches and project work

• Provide feedback to help learners improve their technical and problem-solving skills

• Explain data analytics and Generative AI concepts through practical examples

• Share industry feedback to help improve curriculum and learning content

• Help learners understand how data and AI tools can be applied to real-world problems

What Do You Need to Become a Data Analytics & GenAI Mentor at PW?

The role requires a strong combination of data analytics, business intelligence and Generative AI skills. Candidates should be comfortable working with core data tools, applying statistical concepts and using AI-powered technologies to solve practical data problems. 

1. Advanced Excel

You should have practical knowledge of Power Query, Power Pivot, DAX, complex formulas and dynamic array functions for data analysis and reporting.

2. SQL

You need to understand SQL concepts such as optimised queries, CTEs, Window Functions, and database normalisation.

3. Power BI

Knowledge of DAX, complex measures, dashboard design, Power BI Service, Workspaces and Row-Level Security is relevant for the role.

4. Python for Data Analytics

You should be comfortable using Python libraries such as Pandas and NumPy, along with tools such as Matplotlib and Seaborn for data cleaning, analysis and visualisation.

5. Statistics

A working understanding of descriptive statistics, variance, standard deviation and distributions is required to analyse and interpret data effectively.

6. Generative AI

You should have practical experience using Generative AI tools such as ChatGPT and Gemini for data-related tasks, including code debugging and SQL generation.

7. AI-Powered Analytics

Knowledge of AI-powered tools such as Copilot in Excel and Power BI, GenAI-based ETL and prompt engineering can help in applying AI to data analytics workflows.

Looking to Build Skills for a Data Analytics Career?

If you want to strengthen your skills in data analytics and Generative AI, you can explore programmes that cover data analysis, visualisation, AI tools and practical analytics workflows.

• Want to build skills in data analytics and AI? The Data Analytics With AI programme by PW Skills can help you develop knowledge of data analysis and AI-based workflows.

• Want to learn how Generative AI can be applied to data-focused work? The Data Science With Generative AI programme can help you build an understanding of data science concepts alongside Generative AI applications.

• Want to combine data analytics with Generative AI? The Data Analytics with Gen AI programme can help you explore analytics workflows with Generative AI.

• Want to strengthen your dashboard and spreadsheet skills? The Mastering Data Visualisation With Power BI And MS Excel programme can help you build skills in Power BI and MS Excel, which are relevant to data analysis and reporting.

Check the latest job details and submit your application through the official PW job listing.