The posting
This is where your work makes a difference.
At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond.
Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results.
Here, you will find more than just a job—you will find purpose and pride.
Your role at Baxter
We are seeking an exceptional Senior Data Scientist to join Baxter’s Enterprise Data Analytics team. This strategic role will help transform business functions through advanced analytics, machine learning, Generative AI, Agentic AI, and data-driven decision-making.
As a senior member of the Enterprise Data Science team, you will lead the end-to-end design, development, deployment, and adoption of scalable data science and AI solutions across multiple business domains. You will partner with cross-functional stakeholders to frame high-value opportunities, translate business needs into analytical solutions, and deliver measurable outcomes while promoting responsible AI, engineering excellence, and reusable capabilities.
What you’ll be doing
- Lead the end-to-end lifecycle of advanced analytics, machine learning, Generative AI, and Agentic AI solutions—from opportunity identification and experimentation through production deployment, monitoring, and continuous improvement.
- Translate ambiguous business problems into well-defined data science hypotheses, solution designs, success metrics, and scalable implementation roadmaps.
- Develop and maintain advanced predictive /forecasting models for sales, revenue, expense management, and cash-flow forecasting.
- Design, architect, train, and deploy advanced machine-learning frameworks and traditional time-series models to improve forecast accuracy for sales, revenue, operating expenses, and cash flow.
- Own model validation, explainability, reliability, documentation, monitoring, and governance in line with responsible AI and regulatory expectations.
- Provide technical leadership through architecture reviews, code reviews, mentoring, standards definition, and hands-on resolution of complex analytical challenges.
- Communicate analytical findings, business implications, risks, and recommendations clearly to senior leaders and non-technical stakeholders.
- Foster a mindset of active learning and innovation by exploring emerging AI technologies and adopting solutions that deliver business value.
What you’ll bring
Experience
- Bachelor’s or Master’s degree in computer science, Data Science, Information Technology, or a related technical discipline.
- Minimum 8 years of progressive experience in data science, machine learning, or applied AI, including experience leading complex enterprise initiatives.
- Strong hands-on record of designing, developing, and deploying production-grade machine learning, Generative AI, or Agentic AI solutions.
- Experience working with large, complex, and distributed datasets in enterprise environments.
Core Technical Skills
- Programming and distributed computing: advanced proficiency in Python, SQL, and PySpark, with strong expertise in relevant libraries such as pandas, NumPy, scikit-learn, and NLP libraries.
- Machine learning and statistics: regression, classification, clustering, forecasting, time-series analysis, experimentation, optimization, ensemble methods, and model evaluation.
- Deep learning and Generative AI: hands-on experience with PyTorch or TensorFlow, LLM application patterns, retrieval-augmented generation, prompt engineering, model fine-tuning, evaluation, guardrails, and agentic workflows.
- Hands-on experience building autonomous AI agents and implementing the Model Context Protocol (MCP) or comparable tool-integration patterns.
- Cloud and AI platforms: strong hands-on experience with AWS machine-learning services, including Amazon SageMaker and Amazon Bedrock.
- ML engineering and operationalization: experience packaging, deploying, monitoring, and maintaining production models and AI services using APIs, containers, model registries, automated testing, observability, and retraining workflows.
Domain Experience
- Experience applying data science and AI across Finance, FinTech, Sales, Supply Chain, and Healthcare; ability to transfer methods and insights across domains is essential.
- Ability to explain complex machine-learning outputs, financial drivers, and business implications to cross-functional teams and stakeholders without “black box” ambiguity.
Good to Have
- Experience in healthcare, commercial, supply chain, or financial analytics environments.
- Good understanding of statistical forecasting methodologies, time-series analysis, and error metric evaluations.
- Experience working in Agile delivery models and contributing to product-oriented data science teams.
- Strong business acumen and the ability to translate technical concepts into clear decisions, trade-offs, and outcomes for non-technical stakeholders.
- Certifications: An industry-recognized professional certification in data science or AI, or completion of a top-tier data science executive program, is a strong advantage.
Equal Employment Opportunity
Baxter is an equal opportunity employer. Baxter evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.
Reasonable Accommodations
Baxter is committed to working with and providing reasonable accommodations to individuals with disabilities globally. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application or interview process, please click on the link here and let us know the nature of your request along with your contact information.
Recruitment Fraud Notice
Baxter has discovered incidents of employment scams, where fraudulent parties pose as Baxter employees, recruiters, or other agents, and engage with online job seekers in an attempt to steal personal and/or financial information. To learn how you can protect yourself, review our Recruitment Fraud Notice.
