Data Scientist - Pricings and Promotions

Job Title: Data Scientist - Pricing & Promotions Location: Blackfriars, London (Hybrid - 2 Days Per Week Onsite) Role Type: Contract, £550-650 Per Day (insideIR35), 3 Months Initially (Strong Potential to Extend) The Role We are seeking a commercially minded Data Scientist to optimise pricing and promotional strategies for a leading consumer brand. This role directly supports initiatives that contribute to roughly 20% of total revenue, with a strong focus on analytical rigour, experiment design, and measurable business impact. You will work closely with commercial, marketing, and finance teams to design scalable pricing models, analyse promotional performance, and inform high-stakes decisions that drive growth, profitability, and competitive positioning. What You'll Be Responsible For Promotional Analysis & Strategy • Conduct in-depth analyses of campaign performance to identify trends, opportunities, and areas for optimisation. • Develop and test data-driven promotional strategies that drive customer engagement and commercial uplift. • Measure the success of promotional activities and recommend improvements focused on efficiency and effectiveness. Pricing Optimisation • Design pricing models that balance commercial growth, margin improvement, and competitive positioning. • Use scenario analysis and elasticity modelling to forecast the impact of pricing decisions across products and customer segments. Cross-Functional Impact • Partner with commercial, marketing, and finance teams to translate analytical insights into actionable pricing and promotion strategies. • Contribute to experimentation frameworks, including A/B tests, to validate hypotheses and quantify business outcomes. Must-Have Qualifications • Strong expertise in data analysis and statistical methods (e.g., regression, hypothesis testing). • Proven track record of using data to drive commercial success (e.g., revenue growth, margin improvement, increased market share). • Knowledge of pricing optimisation methods and experimentation frameworks (e.g., elasticity modelling, A/B testing). • Ability to structure complex analytical findings into clear, actionable insights for diverse stakeholders. • Proficiency with SQL (Google SQL preferred) and Python or R for statistical analysis. Nice-to-Have Skills • Experience working within consumer brands or revenue-focused product environments. • Familiarity with large-scale promotional engines or marketing analytics. • Hands-on experience designing end-to-end experimentation workflows. How We Evaluate Candidates Technical Competence: We assess statistical capability, problem-structuring skills, and practical analytical judgment. Candidates must demonstrate proficiency with SQL and Python/R/ through real-world examples. Communication: You must be able to clearly articulate analytical approaches, describe the rationale behind your methods, and explain the commercial impact of your work. Collaboration: We look for candidates who work effectively with commercial stakeholders and can translate data into decisions that move the business forward. If you are interested in applying, please email with your CV and contact number. Desired Skills and Experience Data Science Pricing Optimisation Promotions Analytics Commercial Analytics Revenue Optimisation Statistical Analysis Predictive Modelling Price Elasticity Modelling A/B Testing & Experimentation Regression & Hypothesis Testing SQL (Google BigQuery) Python R Programming Marketing Analytics Campaign Analysis Consumer Insights Business Intelligence Profitability Analysis Scenario Modelling