• Join the Digital Process and Systems Analysis group within Process Development • Provide data infrastructure, platforms, and analytics to support engineering teams across our network • Ensure state-of-the-art data insights to drive innovation and efficiency for the commercialization and optimization of Amgen’s pipeline • Support drug substance development, technology transfer, manufacture, and life-cycle management across Amgen’s global network of manufacturing and development sites • Collaborate as part of a multi-disciplinary team of scientists and engineers • Lead solutions for open-ended challenges, including modeling, data pipelines, and visualizations to support drug substance development, tech transfer, and manufacturing • Contribute to the success of Drug Substance Technology organization by helping to digitize workflows

• Data Management leadership on studies and take responsibility for the development of the project documentation, system set-up, data entry and data validation procedures • Assume responsibility for all DM activities according to client quality expectations • Act as subject matter expert (SME) for DM activities in relationship meetings with Sponsors • Work directly with Sponsors to understand their requirements • Regularly review client specific processes to ensure they remain optimal for Sponsor and Fortrea • Provide guidance, mentoring and training to DM to ensure best working practices are maintained • Lead studies including a combination of healthy volunteer and patient populations • Organize and effectively prioritize workload and deliverables • Be accountable for all DM deliverables as assigned per the established timeline

• Provides CDM leadership for one or more assigned projects or indications. • Lead studies including healthy volunteer and patient populations • Demonstrates leadership and operational expertise in planning and delivery of CDM deliverables • Management and oversight of vendor contracts, resourcing and budget management • Communicates and negotiates effectively with Program level team members. • Primary point of contact for Clinical Data Management (CDM) • Provides oversight and expertise of external service providers or in-house teams • Responsible for proactive risk management and issue resolution/escalation • Develops an understanding of CDASH and SDTM or other recognized industry standards

Title: Generative Artificial Intelligence Senior Data Scientist / Generative Artificial Intelligence Data Scientist Location: - Hartford, CT - Columbus, OH - Charlotte, NC - Chicago, IL Remote Full time Job Description: Sr Data Scientist - GD07AE Data Scientist - GD08AE We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future. Senior Data Scientist - AI Horizontal Products Step into the future with The Hartford as a Senior Data Scientist, where Generative AI is a core strategic capability-it's central to our enterprise strategy. Join a team that's pioneering AI‑driven products across underwriting, claims, and customer service, transforming how we operate and make decisions at scale. As part of our Horizontal AI Products Team, you will investigate emerging models, architectures, and techniques; design rigorous evaluation frameworks; and prototype new products that inform how GenAI is operationalized across the organization. This position is ideal for someone who is intellectually curious, technically deep, and motivated by advancing the state of practice in enterprise Generative AI. This position offers a Hybrid or Remote work arrangement. Candidates living near one of our locations are expected to work in the office three days per week (Tuesday-Thursday). Research & Technical Responsibilities - Conduct applied research in Generative AI, exploring emerging foundation models, architectures, and inference strategies to address enterprise AI use cases. - Lead investigation and experimentation across areas such as: - Agent‑based and multi‑step reasoning workflows - Retrieval‑augmented generation (RAG) - Long‑context modeling and information synthesis - Prompting strategies and controllability of generative outputs - Design and execute rigorous experimental frameworks to evaluate model quality, robustness, latency, cost, and reliability using: - Automated metrics - Human‑in‑the‑loop feedback - LLM‑as‑a‑judge and comparative evaluation methodologies - Create benchmarks and build reproducible pipelines to compare vendor models, open‑source alternatives, and internal approaches. - Rapidly prototype research ideas using modern GenAI tooling such as: - Vertex AI / Google Agent Development Kit - LangChain / LangGraph - RAG frameworks - Hugging Face ecosystems - OpenAI APIs - Translate research findings into deployable GenAI capabilities, working closely with engineering and MLOps teams to ensure scalability, observability, and responsible AI practices. - Contribute to the enterprise GenAI roadmap by identifying gaps, risks, and opportunities informed by ongoing research and industry trends. - Partner with stakeholders across Data Science, Technology, and Business teams to align research directions with real‑world operational challenges. Qualifications - Masters and 5+ years of industry experience OR PhD and 3+ years of industry experience in machine learning or data science and with 1+ years focused on GenAI. - Strong proficiency in Python and modern AI/ML frameworks - Demonstrated experience designing experiments, running evaluations, and drawing conclusions from empirical results. - Hands‑on experience with Generative AI frameworks and platforms, including Vertex AI, ADK, LangChain/LangGraph, RAG pipelines, Hugging Face, and OpenAI APIs. - Deep understanding of: - Agent workflows and tool‑augmented LLMs - Prompt engineering and model controllability - Retrieval‑augmented generation (RAG) design trade‑offs - Generative model evaluation and benchmarking techniques - Experience collaborating with engineering and MLOps teams to transition prototypes into production systems. - Strong written and verbal communication skills, including the ability to explain research findings, limitations, and trade‑offs to both technical and non‑technical audiences. - Authorization to work in the United States without company sponsorship. STEM OPT I‑983 Training Plan endorsement is not supported for this role. Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $90,160 - $166,080 The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience. Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age About Us | Our Culture | What It's Like to Work Here | Perks & Benefits