Applied Data Scientist - Morgan McKinley

Applied Data Scientist - Commercial Analytics & Market Intelligence

Initial 6 month contract | London or Reading - hybrid working | £350pd-£435pd inside IR35

We're partnering with a global organisation seeking a Data Science Engineer to play a key role in shaping data-driven commercial strategy across their Education business. This is a highly impactful opportunity focused on building sophisticated market intelligence and predictive analytics models that directly influence go-to-market strategy, customer growth and long-term revenue planning.

The role sits within a cross-functional environment working closely with Product Marketing, Sales Strategy, Data Engineering and senior business stakeholders to identify untapped market opportunities and optimise commercial performance through advanced analytics and scalable data solutions.

What you'll be doing:

• Design and deliver sophisticated rSAM (Remaining Sales Addressable Market) models to quantify untapped revenue opportunities across global education markets.
• Partner with commercial and product stakeholders to understand complex education-sector dynamics, including subscription models, institutional procurement structures and consortium purchasing behaviours.
• Build scalable end-to-end data pipelines incorporating customer attributes, behavioural signals and predictive model outputs.
• Develop and enhance propensity models to optimise customer acquisition and education-focused sales strategies.
• Deliver strategic insights and market opportunity analysis to senior leadership, supporting commercial planning and data-driven decision making.
• Translate complex analytical findings into clear, actionable business recommendations for both technical and non-technical audiences.

• Experience within Data Science, Analytics Engineering or Commercial Data environments.
• Advanced SQL expertise, ideally working with large-scale datasets within Databricks or similar modern data platforms.
• Strong Python skills for data manipulation, statistical analysis and predictive modelling.
• Proven experience developing and optimising predictive analytics or revenue-driving data science models.
• Experience with propensity modelling or customer growth modelling would be highly beneficial.
• Strong stakeholder engagement skills with the ability to communicate complex insights clearly to senior business audiences.
• Comfortable operating within fast-paced, evolving environments with multiple cross-functional stakeholders.