Senior Level Research Physical Scientist Jobs
Senior level research physical scientist jobs put experienced scientists in charge of research direction, experimental design, and the multidisciplinary teams or projects that deliver results. Most openings are 35% remote or hybrid, concentrated in Technology & Software, Biotechnology & Pharmaceuticals, and Consulting & Professional Services, with employers like Amazon, SentiLink, and St. Jude Children's Research Hospital hiring at this level now.
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Showing 5 of 473+ Senior Level Research Physical Scientist jobs
Job Title: Data Scientist 8+ years
Location: New Jersey
Employment Type: Full-Time
About the Role:
We are seeking a highly skilled and experienced Data Scientist to develop and implement advanced machine learning, statistical modeling, predictive analytics, and AI solutions that drive data-driven business decisions.
Key Responsibilities:
- Develop, train, validate, and deploy machine learning models for classification, regression, clustering, forecasting, recommendation, anomaly detection, and predictive analytics use cases.
- Perform exploratory data analysis (EDA), statistical analysis, data profiling, data preprocessing, data cleansing, and feature engineering to identify meaningful patterns and business insights.
- Build predictive models using Python, Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, and other machine learning frameworks.
- Apply advanced statistical modeling, hypothesis testing, regression analysis, probability, time-series analysis, correlation analysis, and experimental design to solve complex business problems.
- Develop and optimize Deep Learning models using frameworks such as TensorFlow, PyTorch, Keras, and related AI/ML technologies.
- Design and implement Natural Language Processing (NLP) solutions for text classification, sentiment analysis, document processing, information extraction, text summarization, and semantic analysis.
- Work with Generative AI, Large Language Models (LLMs), embeddings, vector databases, prompt engineering, Retrieval-Augmented Generation (RAG), and AI-powered applications where applicable.
- Develop end-to-end data science solutions, from data collection and preprocessing through model development, evaluation, deployment, monitoring, and continuous improvement.
- Evaluate model performance using appropriate evaluation metrics, cross-validation, hyperparameter tuning, model selection, explainability, and statistical validation techniques.
- Implement MLOps practices model versioning, experiment tracking, deployment automation, model monitoring, drift detection, and lifecycle management.
- Work with cloud-based AI/ML platforms such as Microsoft Azure, Azure Machine Learning, Azure Databricks, Azure Data Lake, and Azure Synapse Analytics.
- Develop scalable data processing and machine learning workflows using Apache Spark, PySpark, Databricks, and distributed computing technologies.
- Create dashboards, visualizations, and analytical reports using Power BI, Tableau, Matplotlib, Seaborn, or other visualization tools to communicate insights to business stakeholders.
Required Skills & Qualifications:
- 8+ years of experience in Data Science, Machine Learning, Predictive Analytics, Statistical Modeling, and Advanced Analytics.
- Strong programming expertise in Python, with hands-on experience using Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, and Seaborn.
- Extensive knowledge of Machine Learning algorithms, including Linear/Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost, LightGBM, SVM, K-Means, Clustering, PCA, and Ensemble Methods.
- Hands-on experience with Deep Learning frameworks such as TensorFlow, PyTorch, and Keras, including neural networks and model optimization.
- Experience with Natural Language Processing (NLP), including text classification, sentiment analysis, tokenization, embeddings, transformers, and language models.
- Strong understanding of Generative AI, Large Language Models (LLMs), Prompt Engineering, RAG, Vector Databases, Embeddings, and AI application development.
Job Title: Data Scientist 8+ years
Location: New Jersey
Employment Type: Full-Time
About the Role:
We are seeking a highly skilled and experienced Data Scientist to develop and implement advanced machine learning, statistical modeling, predictive analytics, and AI solutions that drive data-driven business decisions.
Key Responsibilities:
- Develop, train, validate, and deploy machine learning models for classification, regression, clustering, forecasting, recommendation, anomaly detection, and predictive analytics use cases.
- Perform exploratory data analysis (EDA), statistical analysis, data profiling, data preprocessing, data cleansing, and feature engineering to identify meaningful patterns and business insights.
- Build predictive models using Python, Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, and other machine learning frameworks.
- Apply advanced statistical modeling, hypothesis testing, regression analysis, probability, time-series analysis, correlation analysis, and experimental design to solve complex business problems.
- Develop and optimize Deep Learning models using frameworks such as TensorFlow, PyTorch, Keras, and related AI/ML technologies.
- Design and implement Natural Language Processing (NLP) solutions for text classification, sentiment analysis, document processing, information extraction, text summarization, and semantic analysis.
- Work with Generative AI, Large Language Models (LLMs), embeddings, vector databases, prompt engineering, Retrieval-Augmented Generation (RAG), and AI-powered applications where applicable.
- Develop end-to-end data science solutions, from data collection and preprocessing through model development, evaluation, deployment, monitoring, and continuous improvement.
- Evaluate model performance using appropriate evaluation metrics, cross-validation, hyperparameter tuning, model selection, explainability, and statistical validation techniques.
- Implement MLOps practices model versioning, experiment tracking, deployment automation, model monitoring, drift detection, and lifecycle management.
- Work with cloud-based AI/ML platforms such as Microsoft Azure, Azure Machine Learning, Azure Databricks, Azure Data Lake, and Azure Synapse Analytics.
- Develop scalable data processing and machine learning workflows using Apache Spark, PySpark, Databricks, and distributed computing technologies.
- Create dashboards, visualizations, and analytical reports using Power BI, Tableau, Matplotlib, Seaborn, or other visualization tools to communicate insights to business stakeholders.
Required Skills & Qualifications:
- 8+ years of experience in Data Science, Machine Learning, Predictive Analytics, Statistical Modeling, and Advanced Analytics.
- Strong programming expertise in Python, with hands-on experience using Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, and Seaborn.
- Extensive knowledge of Machine Learning algorithms, including Linear/Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost, LightGBM, SVM, K-Means, Clustering, PCA, and Ensemble Methods.
- Hands-on experience with Deep Learning frameworks such as TensorFlow, PyTorch, and Keras, including neural networks and model optimization.
- Experience with Natural Language Processing (NLP), including text classification, sentiment analysis, tokenization, embeddings, transformers, and language models.
- Strong understanding of Generative AI, Large Language Models (LLMs), Prompt Engineering, RAG, Vector Databases, Embeddings, and AI application development.
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Find JobsSenior Level Research Physical Scientist Job Market
Who's Hiring
- Amazon20
- SentiLink15
- St. Jude Children's Research Hospital14
- Langan Engineering and Environmental Services11
- AbbVie10
Top Industries Hiring
- Technology & Software144
- Biotechnology & Pharmaceuticals63
- Consulting & Professional Services43
- Science & Research40
- Healthcare & Medical Services31
Senior Level Research Physical Scientist Jobs: Frequently Asked Questions
How do I get a senior level research physical scientist job?
Employers hiring at the senior level look for candidates who have led original research programs, not just contributed to them. A strong publication record, demonstrated ownership of experimental outcomes, and experience guiding junior scientists all signal readiness. Presenting your work at national conferences and showing cross-functional collaboration with engineers or program managers gives your application a clear edge over equally credentialed peers.
Which companies hire senior level research physical scientists?
Companies hiring senior level research physical scientists right now include Amazon, SentiLink, and St. Jude Children's Research Hospital, based on current listings on Migrate Mate as of November 2026. Hiring at this level typically comes from federal laboratories, aerospace and defense contractors, advanced materials firms, and research-intensive technology companies with dedicated R&D divisions.
Are there remote senior level research physical scientist jobs?
Yes, though availability depends heavily on the nature of the work. About 35% of senior level research physical scientist openings are remote or hybrid as of November 2026, with fully remote roles more common in computational, modeling, or data-intensive specializations than in positions requiring hands-on laboratory or field instrumentation.
What makes a research physical scientist role senior level?
Senior level roles are defined by scope and ownership. Where mid-level scientists execute defined experiments, senior scientists set research objectives, make independent technical decisions, and are accountable for program outcomes. They also mentor junior staff, interface with external partners or funding agencies, and often represent their organization's scientific position in peer review or advisory settings.
Which industries hire the most senior level research physical scientists?
Senior Level research physical scientist roles concentrate in Technology & Software, Biotechnology & Pharmaceuticals, and Consulting & Professional Services, based on current listings on Migrate Mate as of November 2026. These sectors drive demand because they invest heavily in long-cycle R&D programs in areas like quantum sensing, advanced materials, environmental monitoring, and energy systems, where deep physical science expertise is central to the work rather than a supporting function.