Data Scientist (Machine Learning & Generative AI)

Language Models Semantic Kernel Computer Science Machine Learning Telephone Skills Containerization Domain Knowledge Pharmacogenetics Agile Methodology Docker (Software) Unstructured Data Influencing Skills Advanced Analytics Applied Statistics Business Analytics Workflow Management Systems Engineering Amazon Web Services Predictive Modeling Applied Mathematics Feature Engineering Software Engineering Contingent Workforce Lifecycle Management Process Optimization Chemical Engineering Software Documentation Stakeholder Engagement Artificial Intelligence Large Language Modeling Information Architecture Exploratory Data Analysis Data-Driven Decision Making Machine Learning Algorithms Graph Neural Networks (GNNs) Python (Programming Language) Ethical Standards And Conduct Scikit-Learn (Python Package) Influencing Without Authority Cross-Functional Collaboration Keras (Neural Network Library) Microsoft Certified Professional Generative Artificial Intelligence MLOps (Machine Learning Operations) Machine Learning Model Monitoring And Evaluation, As a Senior Data Scientist, you will leverage your expertise in machine learning model development, generative AI, and software engineering to rapidly prototype and deploy advanced analytics products for our manufacturing division. You will collaborate with cross-functional teams, including IT, engineering, and operations, to design and implement robust advanced analytics solutions at scale within production systems. You will also engage in ad-hoc consulting roles to support various projects across the organization. Our data science team contributes to different project phases, from ideation and business case development, through data discovery and preparation, to model development, prototyping, and facilitating adoption., * Independently design and develop innovative quantitative methodologies, leveraging different methods and approaches in machine learning, deep learning, and generative AI, to drive data-driven decision-making and influence key initiatives within the company.

• Apply data science, machine learning, and deep learning techniques to create tools for process monitoring, process optimization, and predictive analytics.
• Develop end-to-end digital solutions, including automation of data workflows and integration into existing systems.
• Engage with customers and stakeholders to understand their needs, requirements, expectations, and potential opportunities, ensuring alignment with business objectives.
• Build and disseminate in-depth domain knowledge of emerging trends in one or more sub-specialty areas of data analytics, fostering collaboration with cross-functional stakeholders.
• Design, lead, and document the development of analytics applications, platforms, and processes to unlock value through scientific insights.
• Stay updated on current best practices, methodologies, and technologies in AI, machine learning, and data science landscape, including compliance and ethical considerations., Language Models Semantic Kernel Computer Science Machine Learning Telephone Skills Containerization Domain Knowledge Pharmacogenetics Agile Methodology Docker (Software) Unstructured Data Influencing Skills Advanced Analytics Applied Statistics Business Analytics Workflow Management Systems Engineering Amazon Web Services Predictive Modeling Applied Mathematics Feature Engineering Software Engineering Contingent Workforce Lifecycle Management Process Optimization Chemical Engineering Software Documentation Stakeholder Engagement Artificial Intelligence Large Language Modeling Information Architecture Exploratory Data Analysis Data-Driven Decision Making Machine Learning Algorithms Graph Neural Networks (GNNs) Python (Programming Language) Ethical Standards And Conduct Scikit-Learn (Python Package) Influencing Without Authority Cross-Functional Collaboration Keras (Neural Network Library) Microsoft Certified Professional Generative Artificial Intelligence MLOps (Machine Learning Operations) Machine Learning Model Monitoring And Evaluation +0

Google IT Automation with Python Senior Data Scientist (Machine Learning & Generative AI) Merck & Co., Inc Rahway, NJ*On-Site CI/CD CrewAI Tooling AutoGen Ideation LangChain Langgraph Pipelines Operations Consulting Automation Innovation Compassion Databricks TensorFlow Agentic AI Mathematics Prototyping Data Mining Simulations Claude Code Data Science Autoencoders Communication Data Analysis Business Case Deep Learning Data Discovery Detail Oriented Computer Vision Cheminformatics Language Models Semantic Kernel Computer Science Machine Learning Telephone Skills Containerization Domain Knowledge Pharmacogenetics Agile Methodology Docker (Software) Unstructured Data Influencing Skills Advanced Analytics Applied Statistics Business Analytics Workflow Management Systems Engineering Amazon Web Services Predictive Modeling Applied Mathematics Feature Engineering Software Engineering Contingent Workforce Lifecycle Management Process Optimization Chemical Engineering Software Documentation Stakeholder Engagement Artificial Intelligence Large Language Modeling Information Architecture Exploratory Data Analysis Data-Driven Decision Making Machine Learning Algorithms Graph Neural Networks (GNNs) Python (Programming Language) Ethical Standards And Conduct Scikit-Learn (Python Package) Influencing Without Authority Cross-Functional Collaboration Keras (Neural Network Library) Microsoft Certified Professional Generative Artificial Intelligence MLOps (Machine Learning Operations) Machine Learning Model Monitoring And Evaluation +0

CrewAI Tooling AutoGen Ideation LangChain Langgraph Pipelines Operations Consulting Automation Innovation Compassion Databricks TensorFlow Agentic AI Mathematics Prototyping Data Mining Simulations Claude Code Data Science Autoencoders Communication Data Analysis Business Case Deep Learning Data Discovery Detail Oriented Computer Vision, * Extensive knowledge of both traditional supervised and unsupervised machine learning algorithms, as well as familiarity with advanced deep learning architectures.

• Proven hands-on experience with Python, including practical skills with libraries such as scikit-learn, Keras, TensorFlow, or PyTorch.
• Familiarity with feature engineering and exploratory data analysis for both structured and unstructured data sets.
• Knowledge of experiment tracking methodologies and tools to monitor model performance and maintain reproducibility.
• Exceptional communication skills to effectively convey complex information to both technical and non-technical stakeholders.
• A strong software engineering mindset, emphasizing the importance of producing high-quality code, documentation, and pipelines.
• A data-centric mindset, focusing on how data can be leveraged to create actionable insights and drive business value.
• Experience working within Agile frameworks and methodologies.

Preferred Qualifications:

• Understanding of generative AI including large language models and vision language models, RAG, pre-training, and/or fine-tuning for specific applications.
• Experience with agents, agentic AI platforms (CrewAI, LangGraph, LangChain, AutoGen, Semantic Kernel, Bedrock, Strands, etc), agent tooling and protocols (MCP, A2A), and/or AI coding tools (Claude Code, Cursor, Codex, Open Claw)
• Familiarity with graph networks, semantic layers, and causal inference.
• Familiarity with deep learning applications or inference, computer vision, autoencoders, etc.
• Familiarity with modern MLOps tools and best practices for lifecycle management including CI/CD pipelines, containerization technologies such as Docker, and deploying machine learning models in cloud environments such as AWS, Databricks, or similar platforms.

Education:

• Bachelor's degree required
• Preferred Ph.D. in chemical engineering, applied mathematics, or other technical fields with expertise in data science and machine learning projects or master's degree in data science, computer science, applied statistics/mathematics, chemical engineering, or a related field with 2+ years of relevant experience in data science and machine learning projects.

Required Skills: Agile Methodology, Agile Methodology, Applied Mathematics, Business Analytics, Business Case Development, Change Catalyst, Chemical Engineering, Cheminformatics, Compliance Analytics, Containerization, Cross-Functional Collaboration, Data Mining, Data Science, Detail-Oriented, Emerging Trends, Generative AI, Information Architecture Design, Information Systems Engineering, Machine Learning (ML), Modeling Simulations, Pharmacogenetics, Predictive Modeling, Prototyping, Software Tool Development, Stakeholder Engagement {+ 2 more}, AutoGen Ideation LangChain Langgraph Pipelines Operations Consulting Automation Innovation Compassion Databricks TensorFlow Agentic AI Mathematics Prototyping Data Mining Simulations Claude Code Data Science Autoencoders Communication Data Analysis Business Case Deep Learning Data Discovery Detail Oriented Computer Vision

We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively.

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The salary range for this role is $129,000.00 - $203,100.00

Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.