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Description
Senior Data Scientist
Work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals.
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.
Responsibilities
• Use statistical analysis to determine which data modeling approach to use, model the algorithm and build a prototype.
• Lead data science projects and partners with cross functional teams to deliver end-to-end advanced analytics/machine learning solution.
• Diagnose business needs, analyze business processes, data flows, IT / technical artifacts and extract understanding of how the system or business process works as input for model development. Translate the business problem into a technical model.
• Identify the data attributes that influence the outcome, define, and monitor metrics, create data narratives, and builds tools to drive decisions.
• Communicate results and statistical concepts to key business leaders.
• Assist in operationalization of the model and develop techniques to improve interpretability of the machine learning outcome.
• Develop A/B testing framework and test model quality.
• Build processes and tools to help monitor and analyze model performance and data accuracy.
• Use 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.
• Work across diverse teams, perspectives and opinions and quickly build consensus.
• Mine and analyze large structured and unstructured datasets.
• Encourage informed risk-taking and act as a catalyst for innovation at Cardinal Health.
Requirements
-Desired Qualifications:
• 7+ years of proven applied Data Science experience and involvement in packaged platform delivery and management.
• Bachelor's degree in Mathematics, Statistics, Engineering, Computer Science, other related field, or equivalent years of relevant work experience is required.
• Master's degree or PhD in related field is highly preferred.
• Business acumen (strong understanding of how business operates, and how to harness data and analytics to meet business needs).
• Strong mathematical and statistical skills.
• Experience with optimization techniques and AI techniques.
• Proficient in feature engineering techniques and exploratory data analysis.
• Experience in statistical and data mining techniques (such as boosting, generalized linear models/regression, random forests, trees, and social network analysis).
• Experience with machine learning techniques such as artificial neural networks, clustering, decision tree learning, and dimensionality reduction.
• Understanding of cloud data engineering and integration concepts.
• Experience with Data Movement Technologies and Cloud Data Warehouse technologies including but not limited to experience with Google Cloud Platform, Big Query, Google Cloud Storage, is preferred.
• Excellent oral and written communication skills.
• Comfortable reading academic research papers and applying them in building models.
• Ability to work independently and within a cross functional team environment.
• Experience with DevOps Agile practices, preferred.
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