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Full Stack Senior Data Scientist - Nationwide

Cardinal Health
Fontana, California, US
$119.8K-$171.1K a year
Permanent

Fuse is on a mission to disrupt healthcare. Our focus on technology, design and a product mindset will help drive that disruption and establish Cardinal Health as a leader in healthcare technology.

Fuse’s innovation culture and modern product development teams power the evolution of our commercial products and spark the creation of new businesses and products.

We leverage technology and insights across the enterprise to solve customer problems and forge new models. Design thinking drives our teams to imagine and invent the next horizon.

It’s more than technology innovation it’s creating new business models beyond our wildest dreams. With a strong leadership team setting the bar high, Fusers are challenged to bring their creativity, technical expertise and diverse perspectives to do the best work of their lives.

Scroll down the page to see all associated job requirements, and any responsibilities successful candidates can expect.

Full Stack Senior Data Scientist is a key role in the transformation of business. They will work closely with business stakeholders to understand their goals and determine how data science can be used to achieve those goals.

They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.

Responsibilities

Data Engineering

  • Experience in building end-to-end ML pipelines from data ingestion, feature engineering, model training, deploying and scaling the model in production.
  • Experience in model training, model optimization, ML system architecture design, and scalable ML model deployment.
  • Build large-scale batch and real-time data pipelines with data processing frameworks like Scio, Google Cloud Platform and the Apache Beam.
  • Proficiency in Python and relevant libraries for machine learning such as scikit-learn and Pandas, as well as Jupyter Notebooks.
  • Experience in building solutions for AI / ML services and platforms with models in production, ML Ops, CI / CD automation of ML pipelines in a cloud-based environment (e.g., GCP).
  • Experience interacting with REST APIs and microservices.
  • Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.

Data Science / Machine Learning

  • Designing and developing machine learning and deep learning solutions and systems.
  • Using statistical analysis to determine data modeling approach, training machine learning tests and experiments.
  • 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 the Fuse landscape.
  • Mine and analyze large structured and unstructured datasets.
  • Identify the data attributes that influence the outcome, define, and monitor metrics, create data narratives, and build tools to drive decisions.

Generative AI

  • Experience working with Generative AI and LLM based solutions.
  • Experience delivering products in Computer Vision, Computational Photography, multimodal-LLMs / Foundation models, Generative AI, Machine Learning (ML), or related areas.
  • Experience working with RAG technologies such as LLM frameworks (Langchain and LLamaIndex), LLM model registries (Hugging Face), LLM APIs, embedding models, prompting techniques (Chain of Thought, ReACT, etc.

and vector databases.

Software Engineering

  • Ensure delivery of architecture patterns that effectively leverage data foundation assets and incorporate API led designs.
  • Build, implement and oversee the implementation of new technologies and API functionality across the organization.
  • Ability to create an end-to-end system architecture for a Data Analytics application.
  • Familiarity with API management platforms like APIGee.
  • Working understanding of software engineering patterns, solutions architecture, information architecture and security architecture with an emphasis on ML / GenAI implementations.

Thought Leadership

  • Lead data science projects and partner with cross-functional teams to deliver end-to-end advanced analytics / machine learning solutions.
  • Work across diverse teams, perspectives and opinions and quickly build consensus.
  • Encourage informed risk-taking and act as a catalyst for innovation at Fuse; generate practical, sustainable and creative options to solve problems and create business opportunities, while maximizing existing resources.
  • Communicate results and statistical concepts to key business leaders.
  • Create visualizations of data that make distributions, trends, and results easy to understand for business leaders.
  • Diagnose business needs, analyze business processes, data flows, IT / technical artifacts and extract understanding of how the system or business process works as input into projects / solutions.
  • Keep up-to-date on current trends and best practices.
  • Identify high-value ML business opportunities and work with Business and IT stakeholders to realize business benefit.
  • Ensure projects are delivered in-line with ML Reference Architecture, road map and to the defined standards and best practices.

What is expected of you and others at this level

  • Apply advanced knowledge and understanding of concepts, principles, and technical capabilities to manage a wide variety of projects.
  • Participate in the development of policies and procedures to achieve specific goals.
  • Recommend new practices, processes, metrics, or models.
  • Work on or may lead complex projects of large scope.
  • Projects may have significant and long-term impact.
  • Provide solutions which may set precedent.
  • Independently determine method for completion of new projects.
  • Receive guidance on overall project objectives.
  • Act as a mentor to less experienced colleagues.

Qualifications

  • Deep knowledge of clinical domain and datasets.
  • Experience in Generative AI, RAG implementation, re-ranking, vector db, embeddings, etc.
  • Proven Machine Learning experience and involvement in data science project or product delivery.
  • Experience with Machine Learning and related technologies such as Tensorflow Python, Torch, Amazon SageMaker, Jupiter Notebooks, git.
  • Understanding of cloud data engineering and integration concepts. Strong mathematical and statistical skills.
  • 10+ years in the Healthcare industry and knowledge of clinical data, preferred.
  • MD, PharmD by training and Healthcare informatics experience, preferred.
  • Delivery experience with Google Cloud Platform, preferred.
  • Delivery of related information software solutions such as data warehouses and integration platforms, preferred.
  • Agile development skills and experience, preferred.
  • Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, other related field, or equivalent years of relevant work experience is preferred.

Advanced technical degree is a major plus.

Anticipated salary range : $119,800 - $171,100

Bonus eligible : Yes

Benefits : Cardinal Health offers a wide variety of benefits and programs to support health and well-being.

  • Medical, dental and vision coverage.
  • Paid time off plan.
  • Health savings account (HSA).
  • 401k savings plan.
  • Access to wages before pay day with myFlexPay.
  • Flexible spending accounts (FSAs).
  • Short- and long-term disability coverage.
  • Work-Life resources.
  • Paid parental leave.
  • Healthy lifestyle programs.

Application window anticipated to close : 07 / 21 / 2024 *if interested in opportunity, please submit application as soon as possible.

The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidate’s geographical location, relevant education, experience and skills and an evaluation of internal pay equity.

Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply.

Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day.

Cardinal Health is an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity / expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.

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15 days ago
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