Lead Commercial Data Scientist, Dow Jones
Business news & financial information publishing
Posted today
Business news & financial information publishing
1001+ employees
Posted today
1001+ employees
Company mission
To deliver trusted news and data to help businesses and society make decisions for a better future.
Role
Who you are
- 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
- 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
What the job involves
- 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
- 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
- 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
- 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
Salary benchmarks
Our take
Dow Jones is a global leader in news and business intelligence, powering a range of well-respected brands, including The Wall Street Journal, Financial News, MarketWatch, and more. The company delivers its content to consumers through a range of formats, such as print, digital, mobile, and live events.
As companies seek to draw Millennials and Gen Z consumers to their platforms, adaptability is vital, since they are driving the demand for innovative tools and techniques, as the world evolves toward the digital-first era. Dow Jones has proven its ability to meet product optimization challenges with its reimagined Factiva offering that includes a list of new features, such as personalized results, an easy-to-use modern interface, and faster free-text search, all with a mobile-first design that adapts to any device.
The company has also focused on new product innovation by expanding its portfolio of capabilities and partnerships, further expanding into AI-powered personalization technologies and ongoing digital transformation. Already a powerhouse in the market, Dow Jones is well set to capitalize on future expansion and innovation opportunities.
Steph
Company Specialist at Welcome to the Jungle
Insights
3% employee growth in 12 months
Company
Company benefits
- 20 weeks of parental leave
- 4 weeks of paid caregiver leave
- Up to 4 weeks of remote work per year
- 1 paid volunteer day annually
- $700 caregiver reimbursement
- Headspace emotional wellness membership
- ClassPass fitness and wellness membership
- Financial rewards for well-being activities
Company HQ
Theater District, New York, NY
Leadership
Almar Latour
(CEO)Before becoming the CEO of Dow Jones and Publisher of The Wall Street Journal, they were the Publisher of Barron’s Group and Executive VP of Dow Jones. They were also the previous Executive Editor of The Wall Street Journal.
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