Bristol Myers Squibb

Director

• Achieve targeted formulary and coverage outcomes within prioritized access accounts in a timely and financially responsible manner
• Develop and execute data-driven, strategically aligned account plans that support enterprise access objectives
• Serve as the primary strategic point of contact for government access customers, engaging key decision-makers and influencers across Medicaid Fee-for-Service organizations
• Lead and coordinate cross-functional collaboration with Policy, Advocacy, HEOR, Reimbursement, Marketing, and Sales partners to advance access goals
• Maintain a deep understanding of account-level policies, formulary review processes, competitive dynamics, decision timelines, and state priorities impacting access
• Proactively identify access opportunities and risks through analysis of market dynamics, policy changes, and performance data
• Monitor, analyze, and communicate contracted product performance and access trends to internal stakeholders
• Effectively manage Medicaid PBA and pooling group relationships, with or without contract solutions
• Translate customer and market insights into actionable strategies that accelerate access and patient impact

Director, Government Market Access

Supply Chain

• Provide a key link in Supply Chain between Customers and Intercompany and third party supply sites and markets
• Manage Operations Liaise with Principal’s Purchasing, Finance Departments and Fiscal Reps to perform Supply Chain Operations activities on their behalf
• Ensure that customer and supply sites comply with Business and Tolling Rules
• Resolve discrepancies in quantity and timing of market orders
• Receipt and entry of market orders as per business rules
• Receipt and process supplier invoices and follow up on price discrepancies, and payment queries
• Accurate receipt and process Tolling Fee invoices
• Perform all activities in accordance to Good Distribution Procedure
• Issue invoices to markets
• Issue required shipping documents, certify with local Chamber of Commerce and legalise with relevant Embassies as required
• Liaise with Freight Forwarder/ Logistics for outbound shipments and update Freight Tracker/ Register if applicable
• Approval or sign off of Redeployment/ Rework on behalf of Principal
• Co-ordinate Redeployments/ Reworks and ensure that the costs are back-charged to the appropriate party
• Liaise with QC for testing, release and generation of CoAs for API if applicable
• Liaise with QC for QP inspection and release of Drug Products
• Manage Information Assist and support Master Data related to customers, contracts and BOMs
• Use reports to monitor and ensure data integrity if applicable
• Receive and forward Customer Complaints as per established procedures
• Follow up and expedite for prompt resolution(s)
• Manage Financial Activities/ Compile Financial Reports
• Perform all SAP transactions in compliant manner
• Meet Finance deadline for month-end and year-end sales reporting
• Provide supporting documentation for Financial Audits as requested
• Work with External Manufacturing organisation to support implementation of new supply models
• Assist in any ad hoc functions as required and/ or any tasks assigned by the Line Supervisor or Line Manager

Supply Chain Operations Specialist

Compliance

• Provision of Quality Compliance support to the Global Operations teams.
• Oversight of Alliance Partners and Third-Party Customers.
• Preparation and oversight of Quality Agreements.
• Support for the Annual Product Review (APQR) process.
• Support for ExM, Enterprise and GBU Quality Council processes.
• Generation, compilation and reporting of metric data to support Global Quality Metric reporting.
• Support preparation, revision, and maintenance of Quality Agreements with CMOs, internal BMS sites, Third Party Customers, and Alliance Partners.
• Provide day-to-day Quality Services support to ExM Operations, including APQR coordination, Quality Agreement activities, and handling quality compliance queries.
• Support compliance tracking activities across the GBU.
• Support ExM, Enterprise, and GBU Quality Council activities by preparing inputs, ensuring metrics availability, and tracking action items.
• Assist in maintaining Quality Services systems (e.g., APQR, Quality Agreements, Quality Council processes) in alignment with procedures and training.
• Support management of relationships with Third Party Customers and Alliance Partners and coordinate quality-related communications such as deviations, change controls, and complaint responses.
• Support Regulatory, CMC, Supply Chain, and other cross-functional partners on filings, renewals, investigations, and product lifecycle activities.
• Compile and report Quality Services metrics and trend data and support continuous improvement activities related to QMS performance.
• Review or assist with review of QMS as assigned and support network-wide continuous improvement initiatives impacting QMS effectiveness, including contributing to GROe assessments.
• Serve as Local Process Owner, as required, with responsibility for assigned Quality Systems (e.g., APQR, Quality Council, Quality Agreements), ensuring procedures, training, metrics, and compliance are maintained.

Manager, Quality Compliance – External Manufacturing

• Drives innovative and efficient study design.
• Develops study designs that address study objectives that will support regulatory approval, medical research and market access.
• Independently leads, initiates, and oversees the statistical support for the development of compounds within a therapeutic area.
• Provides guidance and oversight to statisticians to ensure high quality and timely deliverables.
• Effectively engages as a matrix team member on high level development teams, to act as a scientific and strategic partner in the drug development process.
• Presents and defends complex statistical solutions to all levels of BMS governance, key stakeholders and external regulatory bodies in a clear, concise, complete, and transparent manner that provide influence on key decisions.
• Contributes to Clinical Development Plans, leads GBDS related submission activities, and post-submission strategies/preparations/defenses.
• Provides statistical support and leadership to address health authority requests, publication, presentation, and other public release of information.
• Compliant with BMS processes and SOPs, adherence to global and project standards within an indication or therapeutic area and responsible for quality of deliverable.
• Contributes to creation/maintenance of and provide training on statistical topics departmental SOPs.
• Manages a functional or project budget, and has authority to allocate company resources according to project needs, set priorities, and ensure consistency and adherence to standards therein.
• Represents BMS at professional societies, and in industry-wide technical discussions.
• Contributes to the statistical community of practice.
• Provides active coaching to statistical team members when developing solutions to problems.
• Effectively communicates the DQS Mission and Vision in a fashion that generates pride, excitement and commitment within DQS.
• Fosters a culture of inclusiveness, respect for diversity, compliance with process and allows for the questioning and challenging of others in a respectful and constructive manner.
• Provides leadership to empower and develop the team. Provides guidance to employee's development plans and carries out performance review and feedback. Develops performance metrics for staff.

Director, Biostatistics

Risk

• Develop the Quality Narrative (or equivalent) at a study and/or ASSET and TA level, to document the end-to-end risk-based quality management for CtQ data, processes and vendors demonstrating effective risk and issue management.
• As part of the upstream protocol authoring process, partner with Drug Development, to embed Quality by Design principles and help identify study specific critical to quality (CtQ) data, processes and vendors and ensure adequate risk mitigation strategies have been implemented.
• During trial conduct, provide feedback on risks to study specific critical to quality factors and ensure mitigation strategies are adjusted when new or unanticipated issues arise once the trial has begun.
• This will involve partnering with the CAPA CoE and Serious Breach pillar and Clinical Quality Assurance to gather input from audits, inspections, internal quality events, significant issues, and external intelligence to inform QbD.
• At the study level, conduct quality assurance spot checks to ensure risk mitigation strategies are accurately translated into operational plans.
• Assist the business in defining and establishing Acceptable Ranges/QTL and KRIs for CtQ data.
• Support for cause, critical and/or complex quality issues as well as serious breaches for the TA, where deemed necessary.
• Provide quality and compliance consultation to clinical trials teams throughout study lifecycle.
• Provide regulatory intelligence on current and upcoming regulations to ensure we remain compliant with all applicable requirements.
• Establish strong partnership with business stakeholders.
• Partner with the study teams to ensure effective management of significant quality issues/noncompliance and important protocol deviations for CtQ data, processes and vendors.
• Support the monitoring and evaluation of CtQ factors throughout the study lifecycle and adapt Quality plans accordingly.
• Provide R&D Quality expertise, critical thinking, deliver training and share best practices and lessons learned into future trials.
• Ensure rapid communication and escalation of quality issues, including potential misconduct or issues of significant deviations with project/products, to the business and Health Authorities, as needed.
• Ensure compliance with ICH (E8, E6, E9) and other relevant regulatory requirements.
• External engagement as needed with industry/trade/QA associations, regulatory agencies, vendors, and licensing partners as well as pharmaceutical company peers.

Associate Director, Quality Risk Specialist – GCP

Artificial Intelligence

• Apply, adapt, and in some cases create multi-modal foundation models such as large language models (LLMs), diffusion models, and encoder architectures to answer biological domain-specific questions.
• Address real-world biological modeling challenges such as data sparsity, class imbalance, noise, experimental bias, and heterogeneity of effects.
• Thoughtful model evaluation that incorporates appropriate benchmarks, statistical tests, and problem understanding to support technical and business decisions.
• Work in close collaboration with partners across the organization including wet-lab scientists, Research IT, and other computational scientists to broaden the impact of AI developments.
• Maintain and share up-to-date knowledge of modern advances in the field, including presenting work at public conferences.

Senior Scientist, Predictive Biology – AI

Frontend Engineer

• Own frontend technical delivery for assigned AI Accelerator projects, from rapid prototyping through production-adjacent hardening.
• Build React and TypeScript experiences for chat, copilots, workflow automation, agent supervision, prompt/configuration screens, data apps, and evaluation/feedback workflows.
• Design intuitive interfaces for streaming AI responses, tool execution status, verifiable source references, citations/provenance, confidence displays, multimodal review, human approval steps, and error recovery.
• Build human-in-the-loop experiences that make living context inspectable and correctable by humans, including review, diff, approval, correction, and provenance workflows for agent-maintained knowledge.
• Integrate frontend experiences within BMS-aligned consuming apps and services.
• Define frontend architecture patterns, reusable components, and starter templates that help future Accelerator pods move faster.
• Partner with designers to translate designs, mock ups and living prototypes into accessible, polished, production-quality components and workflows.
• Collaborate with AI, App/Cloud, and Data Engineering teams to define clean API contracts, streaming patterns, auth flows, and telemetry boundaries.
• Build frontends that align with enterprise standards for accessibility, security, input validation, safe rendering, performance, and maintainability.
• Support AI Accelerator agile cycles of six two-week sprints over a 12-week cycle by building, testing, validating, and hardening frontend product increments each sprint.
• Use coding agents and AI-assisted development tools effectively while maintaining strong validation, security, and code quality practices.
• Write and maintain frontend test suites using tools such as Vitest/Jest, React Testing Library, Playwright, Cypress, or similar frameworks.
• Design evaluation interactions and evaluator-facing workflows that allow users and SMEs to score outputs, flag issues, compare variants, capture rationale, and feed lessons back into product and model improvements.
• Instrument user feedback, usage telemetry, and evaluation touchpoints so AI teams can learn where workflows succeed, fail, or need guardrails.
• Contribute to GitHub-based CI/CD, build/release pipelines, environment configuration, and deployment support in partnership with platform teams.
• Partner closely with product owners, scientists, business stakeholders, and engineers to translate ambiguous AI opportunities into usable product experiences.
• Continuously refine frontend priorities and backlog items based on stakeholder feedback, performance results, and lessons learned during MVP development.
• Provide technical coaching through code reviews, design reviews, architecture guidance, and pragmatic delivery standards.
• Help communicate frontend trade-offs clearly to technical and non-technical stakeholders, especially when balancing speed, usability, risk, and enterprise readiness.

Senior Frontend Engineer

AI Engineer

• Design, build, and maintain data pipelines that feed AI Accelerator projects, including ETL workflows, data transformations, and integration with internal and external APIs and data sources.
• Develop and manage relational databases (PostgreSQL/RDS), vector databases (OpenSearch, Milvus, Amazon S3 Vectors), and knowledge graphs (Amazon Neptune, Neo4j).
• Build and operate data infrastructure on AWS, leveraging services such as S3, Athena, RDS, ElastiCache (Redis), and Fargate.
• Build and maintain multi-agent systems using LangGraph, including state management, fan-out/fan-in orchestration, and subgraph composition.
• Develop tool integrations and MCP (Model Context Protocol) servers using FastMCP to enable agent interoperability.
• Implement LLM-powered workflows integrating foundational models (OpenAI, Anthropic, Gemini) via AWS Bedrock and direct API access.
• Build evaluation and observability pipelines using tools such as LangSmith or promptfoo.
• Write and maintain automated test suites (unit, integration, end-to-end) using pytest to ensure reliability of data pipelines and agent workflows.
• Develop evaluation frameworks for LLM outputs, including reference-based metrics and structured output validation.
• Implement data quality checks and validation at system boundaries to catch issues early in the pipeline.
• Support test-driven development practices and contribute to CI test automation.
• Partner with AI Engineers, Pod Leads, and Research scientists to deliver AI Accelerator projects within 12-week cycles.
• Participate in code reviews, design discussions, and technical problem-solving with pod teams.

Application Engineer

• Design, build, and operate backend services, APIs, and application components that power AI Accelerator products.
• Develop Python/FastAPI, TypeScript/Node, or similar services that integrate LLM APIs, retrieval systems, workflow engines, and internal enterprise systems.
• Execute AI Accelerator cycles of six two-week sprints over a 12-week cycle by developing, testing, and validating cloud and agentic AI product increments.
• Develop MCP-accessible services that allow approved agents to read, write, search, and maintain structured (e.g. markdown/YAML) knowledge assets.
• Build MCP/FastMCP read-write-search APIs, permissioned knowledge stores, version control, audit trails, access controls, and integrations with AWS-native storage and identity patterns.
• Implement secure application patterns for authn/authz, BMS SSO, BMS Cloud Creds, secrets management, auditability, input validation, and safe service boundaries.
• Partner with frontend engineers to define clean API contracts, streaming response patterns, error handling, and service-level behaviors for AI-powered user experiences.
• Build and host agentic workflows using LangGraph, including workflow state, multi-agent orchestration, tool execution, fan-out/fan-in patterns, and durable checkpoints.
• Develop MCP tool integrations and FastMCP servers that allow agents to use governed enterprise capabilities safely and consistently.
• Implement retrieval, memory, and context services using AWS-aligned data stores such as S3, Athena, PostgreSQL/RDS, ElastiCache/Redis, OpenSearch, Amazon S3 Vectors, and Amazon Neptune.
• Build and evolve the semantic layer for SQL and other natural-language-to-code generating agents, enabling novel analytical questions to be grounded in query history, column values, warehouse context, explicit instructions, memory, and governed data tools.
• Create and maintain CI/CD pipelines, environment configuration, automated tests, infrastructure-as-code, and release processes for cloud AI applications.
• Instrument application reliability, latency, cost, usage, tracing, and model/agent behavior using enterprise observability and AI evaluation tools such as LangSmith or similar platforms.
• Embedding automated quality gates, security scans, regression tests, structured output validation gates, and responsible AI guardrail checks into delivery pipelines.
• Continuously improve shared platform patterns based on lessons learned across pods, changing enterprise standards, and advances in AI engineering practices.
• Partner with AI Engineers, Data Engineers, Data Scientists, Frontend Engineers, Pod Leads, architects, and product teams to solve complex delivery challenges.
• Help complete MVP transition activities by maturing AI capabilities, adding key features, validating reliability in practice, confirming business value, and assessing production readiness.
• Provide technical coaching through design reviews, code reviews, architecture reviews, incident learning, documentation, and reusable examples.

Senior Application Engineer

• Lead and manage a team of analytical Subject Matter Experts (SME) responsible for the commercial drug product release methods utilized in the cellular biology, molecular and flow cytometry areas.
• Provide technical oversight and guidance to team as needed in support of method performance troubleshooting, evaluation of analytical test methods and data generated by internal and external laboratories, including investigations related to out of specification, out of trend, and aberrant results.
• Oversee method performance metrics and the team’s completion of quality events including actions and investigations within electronic systems.
• Act as a Subject Matter Expert (SME) in functional areas as needed.
• Partner with analytical development and the commercial QC organization to identify method optimization and automation opportunities to enhance productivity and reduce the cost of product testing.
• Interface with analytical development functions on method qualification strategies.
• Hire, mentor, and develop exceptional ASAT personnel.

Associate Director, Drug Product Analytical Science and Technology

Research Scientist

• The Principal Scientist is a highly experienced subject matter expert responsible for leading method optimization, transfer, and validation in support of Cell Therapy analytical portfolio.
• Conceptualize and lead complex projects, provides strategic scientific and technical input to the programs and projects.
• Apply technical knowledge, regulatory requirements, and scientific principles to independently perform complex troubleshooting and problem solving.
• Balance deep hands-on laboratory involvement with cross-functional leadership, mentoring, and external scientific engagement.
• Represent the department in product review boards, regulatory inspections (internal and external audits).
• Own and author relevant analytical sections of regulatory submission and responses to health authority questions and requests.

Principal Scientist, Analytical Science and Technology, Cell Therapy

Data Scientist

• Frame ambiguous business and scientific questions into measurable AI product hypotheses, success metrics, evaluation plans, and rapid experiments.
• Contribute to six-sprint, 12-week AI Accelerator agile cycles by testing hypotheses, validating AI product increments, and adapting analyses during two-week sprints.
• Build data science prototypes using Python, SQL, notebooks, APIs, and AWS-aligned data services.
• Support sandboxed data problem solving in non-production environments, enabling agents and analysts to branch, transform, test, and audit code-plus-data experiments before promotion.
• Evaluate and curate the analytical context agents and analysts rely on, including explicit instructions, memory, data tools, and curated meaning from source materials and recommend improvements based on measured impact on agent quality.
• Develop analytical features, embeddings, classifiers, ranking/scoring methods, recommendation logic, simulation approaches, or optimization methods as needed for product outcomes.
• Partner with Data Engineers to shape reliable datasets, retrieval corpora, metadata, and feature pipelines using S3, Athena, PostgreSQL/RDS, vector databases, and knowledge graphs.
• Design and execute evaluations for LLM, RAG, and agentic workflows, with emphasis on context quality, knowledge curation, semantic evolution, and model quality.
• Build evaluation rubrics, golden datasets, structured output validation, error taxonomies, hallucination risk measurement, and SME review loops.
• Use tools such as LangGraph, LangSmith, PydanticAI, or similar frameworks to test agent behavior, retrieval quality, reasoning traces, and workflow reliability.
• Evaluate whether curated enterprise context improves agent quality, reliability, traceability, and decision usefulness compared with raw document retrieval.
• Assess model and agent outputs for quality, uncertainty, calibration, bias, hallucination risk, traceability, and fitness for intended use.
• Explore approved proprietary and open model options through enterprise channels and recommend model/task pairings based on evidence, risk, cost, and performance.
• Define KPIs and analytical measurement plans for AI products, including adoption, user behavior, workflow efficiency, scientific utility, and business value.
• Use bi-weekly demos, sprint reviews, stakeholder feedback, and performance results to measure MVP progress and assess readiness for scaling or production transition.
• Apply statistical modeling, experimental design, causal inference, or quasi-experimental methods where appropriate to separate signal from noise.
• Create clear analyses, visualizations, and narratives that help product teams and stakeholders understand model behavior, limitations, and opportunities.
• Partner with responsible AI, security, quality, and domain experts to ensure evaluations and analytics respect data privacy, scientific integrity, and enterprise governance.
• Contribute reusable notebooks, context-quality evaluation harnesses, analytics templates, prompt/evaluation assets, and data science patterns that can be adopted across pods.
• Participate in code reviews, analysis reviews, design discussions, and technical problem-solving with engineering and product teams.
• Use coding agents and AI-assisted development tools effectively while validating outputs, documenting assumptions, and maintaining scientific rigor.
• Continuously refine analytical priorities and backlogs as insights emerge, incorporating stakeholder input, performance results, and lessons learned throughout MVP development.
• Coach peers on practical data science, evaluation design, measurement strategy, and evidence-based decision making in fast-moving AI delivery environments.

Senior Data Scientist

Therapist

• Provide bioassay, flow cytometry and/or molecular biology analytical expertise in support of QC lab investigations.
• This encompasses supporting technical investigations to identify root cause and provide corrective and preventive actions, including method remediations and experimental studies at the bench.
• In accordance with established protocols and research objectives, independently execute experimental work with a high degree of technical proficiency, contribute to data analysis and documentation, and collaborate within cross-functional teams.
• Contribute to the development and optimization of new and existing laboratory methods and protocols.
• Present experimental findings and progress updates to immediate team.
• Support the preparation of internal technical reports and presentations as appropriate.
• Support transfer of commercial methods and method validation in compliance with global regulatory requirements.
• Responsible for the stewardship of bioassay, flow cytometry and/or molecular methods in the Cell Therapy Quality organization.
• Implement method lifecycle and method maintenance programs to support bioassay, flow cytometry and/or molecular biology methods in support of cell therapy drug products.
• Author, revise, and review technical documents such as test methods, SOPs, trend reports, and/or investigation reports as appropriate.
• May lead project, CAPA and deviation/investigation related tasks and/or continuous improvement efforts.
• May provide support in the authoring of the analytical sections of regulatory submissions, responding to health authority questions and functioning as the method validation and method transfer expert during inspections as required.
• May partner with development organizations in the design of development and qualification studies, selection and characterization of reagents, and method optimization initiatives.
• Perform other tasks as assigned.

Scientist, Analytical Science and Technology – Cell Therapy

Operations

• The MSL is responsible for identifying disease and product related medical needs in a defined geography.
• The primary role of the MSL is to develop and maintain relationships with Thought Leaders (TL) and Healthcare Providers (HCP) within their territory.
• Engage in meaningful scientific exchange that will ensure patients have access to BMS medicines.
• Facilitate research and serve as the medical resource for external stakeholders in the community.
• Develop geography-specific Field Medical and TL Interaction plans based on therapeutic area objectives and TLs needs.
• Adopt institution/account planning approach and contribute to cross-functional institution/account plans.

Medical Science Liaison, Neuropsychiatry

• Develop the Quality Narrative (or equivalent) at a study and/or ASSET and TA level, to document the end-to-end risk-based quality management for CtQ data, processes and vendors demonstrating effective risk and issue management.
• Provide quality and compliance consultation to clinical trials teams throughout study lifecycle and establish a feedback loop to ensure mitigation strategies are adjusted when new or unanticipated issues arise once the trial has begun.
• As part of the upstream protocol authoring process, partner with Drug Development to embed Quality by Design principles and help identify study specific critical to quality (CtQ) data, processes and vendors and ensure adequate risk mitigation strategies have been implemented.
• During trial conduct, provide feedback on risks to study specific critical to quality factors and ensure mitigation strategies are adjusted when new or unanticipated issues arise once the trial has begun.
• Conduct spot checks to ensure risk mitigation strategies are accurately translated into operational plans.
• Assist the business in defining and establishing Acceptable Ranges/QTL and KRIs for CtQ data.
• Provide regulatory intelligence on current and upcoming regulations to ensure we remain compliant with all applicable requirements.
• Support the monitoring and evaluation of CtQ factors throughout the study lifecycle and adapt Quality plans accordingly.
• Provide R&D Quality expertise, critical thinking, deliver training and share best practices and lessons learned into future trials.