Data Scientist [Quedan 3 Días]

About Our Organization :

Dow Jones is a global provider of news and business information, delivering content to consumers and organizations around the world across multiple formats, including print, digital, mobile and live events. Dow Jones has produced unrivaled quality content for more than 130 years and today has one of the world’s largest news-gathering operations globally. It is home to leading publications and products including the flagship Wall Street Journal, America’s largest newspaper by paid circulation; Barron’s, MarketWatch, Mansion Global, Financial News, Investor’s Business Daily, Factiva, Dow Jones Risk & Compliance, Dow Jones Newswires, OPIS and Chemical Market Analytics. Dow Jones is a division of News Corp (Nasdaq : NWS, NWSA; ASX : NWS, NWSLV).

About the Role :

Dow Jones is seeking a skilled Data Scientist to join our AI Engineering Team. You will design, construct, and maintain machine learning pipelines tailored for various AI applications, particularly focusing on Natural Language Processing. Collaborating with our engineering team, you'll integrate machine learning models, optimize performance, and ensure effective real-world application of machine learning solutions.

As a key team member, you will be involved in every aspect of the data science project development process, from data analysis and model selection to building proofs of concept and refining pipelines. You will leverage your expertise in statistical analysis and machine learning techniques to derive insights from data, address the organization's needs, and deliver tangible value through actionable outcomes.

You Will :

• Collaborate within the AI Engineering Team to maintain robust data pipelines supporting various ML models, focusing on information retrieval applications.
• Analyze and clean large datasets to optimize reusable ML models.
• Partner with stakeholders across the company to translate business requirements into technical solutions.
• Utilize analytical skills for NLP modeling, algorithm selection, and POC development.
• Develop data enrichment pipelines to enhance insights aligned with strategic objectives.
• Collaborate with cross-functional teams to address the organization's data-driven needs, managing significant volumes of structured and unstructured data.
• Integrate diverse ML models into systems, ensuring interoperability and performance optimization.
• Lead efforts to optimize ML model performance through data analysis and validation in real-world applications.
• Stay updated on AI, ML, and NLP advancements, incorporating emerging trends into processes.

You Have :

Our Benefits :