Lead Commercial Data Scientist at Dow Jones · London

Lead Commercial Data Scientist Location: London-1 London Bridge St Job Description: Lead Commercial Data Scientist – Dow Jones Energy Role Summary We are seeking a Senior Commercial Data Scientist to lead the creation, development, and deployment of predictive intelligence models that power the commercial strategy for Dow Jones Energy. In this specialized, highly commercial role, you will move beyond standard data insights to build production-grade machine learning algorithms that tell our global sales teams exactly who to call, when to call them, what product to pitch, and at what price. You will sit directly alongside Global Sales Directors, Account Executives, and Revenue Operations leaders, transforming complex client usage data and market signals into a highly automated, hyper-targeted sales pipeline engine. In This Role, You Will: Sales Acceleration & Predictive Pipeline Modeling Build and productionise predictive deal-scoring models that analyze historical win rates, engagement data, and market triggers to rank inbound leads for and White Space opportunities for Sales. Develop "Next-Best-Action" recommendation algorithms integrated directly into Salesforce, providing Account Executives with automated, real-time prompts for the highest-value upsell and cross-sell angles. Architect automated account health dashboards that translate complex institutional API and software usage patterns into scannable sales alerts, flagging high-risk client contraction or accounts primed for expansion. Engineer white-space & TAM analysis models to systematically audit the global commodity market, identifying untapped logos and potential enterprise customers currently missing from our pipeline. Pricing Algorithm Optimization & Revenue Defense Design dynamic price elasticity and optimization models that simulate client price tolerance across various customer segments to maximize ARR during annual renewals. Develop contract value simulation matrices that arm Account Executives with data-backed parameters for high-stakes enterprise negotiations, protecting pricing boundaries. Quantify the specific commercial revenue upside of raw feature updates or new energy index methodologies, telling product and sales leaders exactly how to monetize new data assets. Cross-Functional Sales Enablement & Engineering Partner directly with Sales/Revenue Operations and Data Engineering to build, maintain, and clean automated sales data pipelines within cloud environments (e.g., Snowflake, Databricks). Translate highly intricate mathematical models into intuitive, low-jargon dashboards, training global commercial teams to trust and execute on data-driven sales leads. Establish rigorous data quality loops ensuring that automated alerts pushed to the sales floor are completely accurate and actionable, directly maintaining trust in internal forecasting tools. You Have Education: Master’s or Ph.D. in Data Science, Quantitative Finance, Statistics, Economics, Business Analytics, or a closely related quantitative field. Experience: 5+ years of practical data science experience, with a heavy emphasis on sales intelligence, revenue analytics, or go-to-market data science inside a B2B SaaS, FinTech, or Price Reporting Agency (PRA) setting. Technical Stack: Advanced mastery of Python or R, production-grade SQL, and deep experience linking machine learning workflows to Salesforce CRM via automated APIs. Methodology Expertise: Proven skill in supervised classification (lead scoring), predictive churn forecasting, customer segmentation (clustering), and value-based price optimization modeling. Domain Knowledge: High comfort with the enterprise sales funnel (pipelines, conversion rates, ARR, net revenue retention) alongside an interest in physical energy and chemical supply chains. Success Profile Sales-First Mindset: Driven by the thrill of closed deals and absolute pipeline growth, seeing math as the ultimate tool to unlock hidden commercial revenue. Elite Communicator & Collaborator: Able to collaborate effectively in a matrix environment and to stand in front of a global sales floor or senior revenue executives and explain advanced data science models using simple, highly motivating language. Fast-Paced Operator: Comfortable deploying iterations quickly, prioritizing rapid sales-enablement wins without sacrificing the absolute integrity of the underlying code. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic under applicable law. Reasonable Accommodation We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process. If you need assistance or accommodation in completing your application or participating in an interview due to a disability, email us at talentresourceteam@dowjones.com. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates. Please refer to the privacy notice at the bottom of this page for submitting any data access, deletion, or other data subject rights requests, where permitted under your local laws and regulations. Business Area: Dow Jones - Energy Job Category: Data Analytics/Warehousing & Business Intelligence Union Status: Non-Union role