Zoetis · 3 days ago

Data Scientist

Kalamazoo, MI

Full-time

Onsite

Senior Level

$100K/yr - $144K/yr

5+ years exp

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AgricultureBiotechnology

Comp. & Benefits

Insider Connection @Zoetis

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Apply data science methods including statistical modeling, machine learning, deep learning, and digital signal processing to solve prioritized, business problems

Effectively document and test data science models, methods, and code

Follow data analytics quality and security standards for data science work

Collaborate with product and technology teams to test and deploy algorithms or data products into the production environment

Develop a superb understanding of the business domain(s) to uncover new applications for data science

Research new technology developments in related fields and champion their introductions to the organization by developing proof-of-concepts and prototypes

Qualification

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Pharmaceutical IndustryAnalytics AlgorithmsBig Data ProcessingMATLABRPythonStatisticsMachine LearningDeep LearningSQLData EngineeringETLML OpsSource ControlGitGitHubProject ManagementProblem-SolvingCommunicationTeamworkTime ManagementTensorFlowTheanoTorchImage DataVideo DataIoTSignal ProcessingCloud-Based Event Stream ProcessingOperations Research

Required

MS degree in Engineering, Mathematics, Computer Science, or Physics; PhD is preferred.

Minimum 5 years of industry experience; familiarity with pharmaceutical, biopharmaceutical or other process industry is a plus.

Minimum 4 years of experience designing and implementing analytics algorithms, processing large datasets, deploying data products.

Experience analyzing large structured and unstructured datasets with MATLAB, R, Python or similar high-level tools, using big data sources (ADLS, Spark, MongoDB, relational, graph, etc.)

Proficiency in the areas of statistics, machine learning, and deep learning; along with their implementation in analytics tools and technologies, including at a minimum Python, R, and SQL

Comprehensive understanding of data engineering, including data extraction, transformation, and loading (ETL) and Machine Learning (ML) Ops concepts

Comprehensive understanding of source control and collaboration tools, such as Git and GitHub Enterprise

Excellent communicator, adept at explaining complex topics to non-technical audiences.

Ability to drive a project and work both independently and in a team.

Committed to delivering high-quality work within established timelines and capable of prioritizing tasks across multiple projects.