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AI and Data Engineer

Bristol Myers Squibb
Full-time
Remote friendly (Madison, NJ)
United States
IT

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Role Summary

AI and Data Engineer role focused on development and deployment of scalable AI solutions to support business functions. Collaborates with cross-functional teams to translate requirements into technical specifications, develop AI tools and frameworks, and provide AI-driven insights to inform strategic decisions.

Responsibilities

  • Development and implementation of scalable AI solutions to address complex business challenges in Finance, HR, Law, Compliance and Learning.
  • Develop new AI/Gen AI tools aligned with business objectives and ensure they are operationalized effectively.
  • Build and optimize AI agents that can autonomously handle complex tasks, make decisions, and deliver insights in real-time.
  • Develop, integrate, and continuously improve AI-powered chatbots and virtual assistants to support employees across various teams.
  • Focus on augmenting the decision-making capabilities of leadership teams by providing AI-powered insights that inform strategic initiatives for BMS.
  • Collaborate with cross-functional teams to translate business requirements into technical specifications and solutions.
  • Conduct thorough testing and validation of AI models to ensure accuracy and reliability.
  • Develop standard AI frameworks for streamlined deployment practices.
  • Establish and maintain consistent documentation of AI capabilities.
  • Work closely with data & analytics, technology teams and business stakeholders across Enabling Functions to ensure alignment on AI initiatives and goals.
  • Use data storytelling techniques when presenting to business stakeholders to clearly communicate technical value provided.
  • Help develop standardized capabilities and best practices within the AI development space.
  • Contribute to the standardization of AI deployment methodologies.
  • Ensure adherence to operating policies and drive a culture of analytics and fact-based decision making.

Qualifications

  • Minimum of 2 years of hands-on experience working in AI or ML, data science, data integration, and reporting.
  • Minimum of 1 year of hands-on experience working with LLMs.
  • Bachelor's degree in computer science, information systems, computer engineering, or equivalent.
  • Experience with cloud-based environments (AWS, Azure, Google AI, etc.).
  • Proficiency in Python/R and SQL.
  • Hands-on experience with designing and deploying machine learning models using Scikit-Learn, TensorFlow, PyTorch, etc.
  • Experience with Git.
  • Excellent communication and presentation skills. Proven ability to explain complex analyses and outcomes to both technical and non-technical stakeholders.
  • Ability to work collaboratively with technical peers across locations (US, EU, India).

Preferred Qualifications

  • Master's degree in computer science, information systems, computer engineering, data science, or related technical field.
  • Experience with AI applications in a regulated environment (health care, biotech, pharmaceuticals).
  • Proven track record of development of AI projects from conception to deployment, including stakeholder management and delivering impactful results.
  • Familiarity with additional AI frameworks and tools beyond those listed (e.g., Agentic, LLMs, Computer Vision, text-to-code).
  • Experience with Agile methodologies and tools (e.g., JIRA, Confluence).

Experience

  • Excellent interpersonal, collaborative, team-building, and communication skills for effective collaboration within matrix teams.
  • Strong analytical skills with substantial knowledge of AI.
  • Ability to quickly gain and apply functional area-specific knowledge.
  • Experience interpreting analytical results and translating insights into business implications.
  • Experience interacting with business stakeholders to understand, anticipate, and fulfill analytical information requirements.
  • Creative problem-solving skills to answer key business questions.
  • Ability to work with diverse teams across organizational lines and structures.
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