• Develop scripts and automations in Python / PySpark / SQL to modernize legacy processes (database management, rules, and alert engine), reducing manual effort and increasing traceability. • Develop end-to-end Machine Learning models: scoping, exploration, feature engineering, model selection/evaluation/interpretation, production deployment, monitoring and retraining. • Work with large volumes of data in distributed environments (Spark), with a focus on performance and data quality.

- Elsevier, Inc. - Data Scientist III - 1600 John F. Kennedy Blvd., Suite 1800, Philadelphia, PA 19103 JOB DESCRIPTION: - Support our Data Sciences team within Health Content Operations and work with the Clinical Solutions and Education business units to provide research around data science and analytics that drives growth, revenue generation, outreach, and innovation. Focus on solving data science problems such as entity extraction, named-entity recognition, word-sense disambiguation, information retrieval, clustering, supervised and unsupervised learning using NLP, machine learning, deep learning, and statistical methods. Compare and recommend the use of latest GenAI technologies to solve these problems when the traditional approaches cannot solve them. Drive innovation by leveraging the latest research, literature, latest developments in GenAI, Responsible AI, GenAI Evaluation, RAG to Build POC’s and solve complex problems. Collaborate with inter disciplinary teams across organization to build solutions. Conduct research on concept indexing, relationship extraction, and data extraction from clinical data and scientific literature. Analyze vast amounts of unstructured data and design, prototype, and operationalize machine learning and automation solutions for our health business. Provide data analytics support including designing automated approaches for ontology and graph development, ontology validation and terminology mappings. Analyze extracted information to drive such processes as automated and manual data cleansing, linking, and populating knowledge graphs. Coordinate with stakeholders as needed. Manage contractors as needed to get new entities reviewed for ingestion into Emmet. Ensure compliance with DPR documentation. Lead the Rising Tide program and Mentor interns. Coordinate with IT developers and (content) subject matters experts to translate information needs into data science solutions. Drive new developments and implement process changes and disruptive technologies in the organization. Perform other duties as needed. REQUIREMENTS: - Master’s degree (or foreign equivalent) in Data Science, Data Analytics, Enterprise Intelligence, or a related field required. - 2 years of experience in job offered or related occupations required. - Also required is: 2 years of experience: with doctor, nurse, and patient information needs to design Data Science, Machine Learning (ML) and Natural Language Processing (NLP) solutions to improve patient outcomes; working with deep learning models, neural networks, and state-of-the-art transformer language models, putting data science into production; utilizing nix systems, open-source software, Jupyter notebook hubs, cloud computing, MATLAB for data modeling, machine learning and visualization purposes, and Java, Python or R; and with utilization of database, data manipulation, and visualization tools, such as MySQL, Excel, and Tableau. - Employee reports to Elsevier, Inc. office in Philadelphia, PA but may telecommute from any location within the U.S. - Experience can be concurrent. SALARY RANGE FOR REQ# R111460 : - $110,487.22 to $115,600/year + standard company benefits - This salary range is specifically for REQ#R111460. Salary range listed below is general and covers all similar positions in the area and should not be considered for this specific position. HOW TO APPLY: - Interested candidates should send email to ResumesICT@RELX.com and reference job code: R111460 #LI-DNI #IND-DNS #ICT U.S. National Base Pay Range: $78,800 - $131,300. Geographic differentials may apply in some locations to better reflect local market rates. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

• Build, lead, and mentor a high-performing data science team across analytics, experimentation, and statistical modeling. • Personally drive and guide impactful IC work, from ad hoc analysis to ML-based modeling projects. • Create and evangelize best practices for data reliability, reproducibility, and documentation. • Collaborate with senior leadership to define a long term data strategy • Own and scale the Data Science function across product, growth, and go-to-market, aligning with company OKRs and strategic bets. • Hire, lead, and mentor a world-class team of data scientists and analysts; build a high-trust, high-impact culture grounded in intellectual rigor and bias for action. • Define and communicate Render’s long-term data strategy and architecture in partnership with Engineering and Product leadership. • Drive strategic insight across the org: from pricing and packaging to product adoption, conversion, and customer segmentation. • Promote data fluency across Render through tools, dashboards, and processes that empower every team to make smarter decisions • Provide actionable insights about our users such as how they work, how they discover features, and which obstacles they might run into on the platform. • Contribute toward initiatives to enhance the reliability and accuracy of our data infrastructure and processes.

• Collaborate closely with our customers, engineering, product, and security teams to operationalize vulnerability models, ensuring scalability, reliability, and alignment with customer needs. • Lead discovery and prioritization of customer security data sources (asset inventory, vuln scanners, EDR, IAM, CMDB, cloud posture, ticketing, external attack surface, threat intel), including feasibility, value, and effort trade-offs. • Apply exposure-management domain expertise to ensure data supports actionable use cases (attack surface reduction, vulnerability prioritization, remediation workflows, risk acceptance, SLA tracking). • Partner with engineering to design and validate ingestion pipelines (APIs, exports, streaming/batch), ensuring reliability, observability, and secure handling of customer data. • Perform pragmatic data analysis to diagnose data issues and quantify impact (completeness, accuracy, timeliness, consistency), and recommend remediation steps to customers and internal teams. • Define and maintain customer-facing technical documentation: integration guides, data dictionaries, validation checklists, and runbooks for common ingestion and modeling issues. • Collect, clean, explore, analyze, and normalize various security data sources. • Stay current on exposure-management practices, vulnerability intelligence, attacker tradecraft, and the relevant vendor ecosystem to inform integrations and customer guidance.