Data Scientist - Machine Learning Architect
Enterprise Architecture (EA) group creates technical strategies and road maps to meet current and anticipated business need as efficiently as possible adding speed and optimal-cost solutions in support of our growing business. The Information and Machine Learning (ML) Architecture group within EA supports business innovation by pursuing emerging technologies (such as ML) and turning them into differentiating business capabilities.
Identify opportunities for Cardinal Health to expand horizontally or vertically and expand our role in the healthcare ecosystem. Create and deliver new / enhanced business value at Cardinal Health by influencing and leading change of the Machine Leaning domain across Business and IT. Establish a deep understanding of the functional and technical aspects of Machine Learning in order to create architectures, establish frameworks, guide project decisions, designs and investment to increase speed to market and efficiency of changes.
Contributes to the EA and Enterprise Information Technology as a visible technical leader by contributing to talent acquisition and development; establishing new & innovative solutions to maximize business value and effectiveness as well as contributing to areas outside area of responsibility when needed.
Ideal candidate has a blend of data science, software engineering with a strong background in data.
- Designing and developing machine learning and deep learning solutions and systems.
- Implementing appropriate ML algorithms. Running / training machine learning tests and experiments.
- Take current problem domain and architect / design solutions that solve immediate business need, meet current standards and support principles and related reference architectures.
- Diagnose business need, analyze business process, data flows, IT / technical artifacts and extract understanding of how the system or business process works as input into projects / solutions.
- Work across diverse teams, perspectives and opinions and quickly build consensus.
- Uses deep subject matter/functional expertise, influence and process skills to help internal/external customers and stakeholders identify and meet their high priority needs while considering cultural and diversity implications.
- Encourages informed risk-taking and acts as a catalyst for innovation at Cardinal Health; generates practical, sustainable and creative options to solve problems and create business opportunities, while maximizing existing resources.
- Proactively develops, maintains and evangelizes technical knowledge in Machine Learning and adjacent technologies. Keeps up-to-date on current trends and best practices.
- Performs assessments and listens to internal/external customers to understand and anticipate their needs and determine their priorities in the context of the overall enterprise.
Accountabilities in this role:
- Possess deep functional and technical understanding of the Machine Learning technologies (Google’s Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across Cardinal Health’s large, complex and diverse landscape.
- Identify high-value ML business opportunities and work with Business and IT stakeholders to realize business benefit.
- Scale Machine Leaning expertise and practice throughout Cardinal Health.
- Establish development and delivery best practices in order for ML implementations to minimize rework and maintenance cost. Build ML architectures that work at Cardinal Health scale.
- Assist in implementation of ML related efforts to ensure their operational viability.
- Establish buy vs build guidance.
- Assist skill uplift across the IT enterprise.
- Lead selected projects in order to translate business requirements into technical specifications and implementation detail.
- Understand and enable Cardinal Health business via an efficient and effective ML practice that provides ML solutions and outcomes at the most efficient cost.
- Ensure effective designs and quality deliverables in the ML space by designing and developing machine learning and deep learning systems, running machine learning tests and experiments, implementing appropriate ML algorithms
- Maintain a solid understanding of up and downstream impacts implementing solutions using ML technologies.
- Troubleshoot technical issues within ML platforms when needed.
- Engage early in project efforts in order to analyze current solutions, provide solution options and recommendations, understand business process impact, provide accurate estimates.
- Aide adoption of ML solutions within the business by conducting training, coordinating demos.
- Support and influence delivery operations within platforms by continually looking for opportunities to streamline delivery, increase business value and measure platform value via metrics and measures.
- Build ML solution architectures (often incrementally) that aligns requirements, reference architectures design patterns and technology standards to achieve solution agility and speed to implementation.
- Weigh Risk & ROI against schedule & budget considerations and provides solution recommendations.
- Ensure projects are delivered in-line with ML Reference Architecture, road map and to the defined standards and best practices.
- Partner with PMO, EA, Shared Services, SAP CoE and project teams to develop and implement plans and procedures to achieve ML Solution delivery goals.
- Support the creation of IT strategies and road maps within the ML domain based on business strategy, business and IT trends, and current and future architectures.
- Effectively communicate and influence others towards future state solutions and architectures. Evangelize the purpose and value of Machine Learning solutions.
- Partner with application, information, integration, and infrastructure architects to help position appropriate usage of technology for segment solutions.
- Performs complex analysis of system capabilities and provides consultation on ML solutions to various stake holders.
- Proven Machine Learning experience and involvement in packaged platform delivery and management.
- Experience with Machine Learning and related technologies such as Tensorflow Python, Torch, Amazon SageMaker, Jupiter Notebooks.
- Proven experience as a tech lead or architect.
- Understanding of data engineering and integration concepts.
- Masters Machine Learning, PhD in Physics, Economics, Applied Mathematics, Computer Science, ML.
- 3+ years in the distribution or Healthcare industry and knowledge of their business practices.
- Delivery experience with Google Cloud Platform.
- Delivery of related information software solutions such as data warehouses and integration platforms.
- Agile development skills and experience.
Education or Equivalent:
- Undergraduate degree in computer science, mathematics or related field. An MBA or advanced technical degree is a major plus.
Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.