Responsibilities : • Work with product managers, data scientists, ML engineers, and other ... model development, experimentation, and integration with OpenAI API. • Extensive hands-on ...
Responsibilities : • Work with product managers, data scientists, ML engineers, and other ... model development, experimentation, and integration with OpenAI API. • Extensive hands-on ...
Research Scientist - Biochemistry This role offers an opportunity for a biochemist to join a ... Analyze experimental data using appropriate curve-fitting and data analysis software, interpret ...
Research Scientist - Biochemistry This role offers an opportunity for a biochemist to join a ... Analyze experimental data using appropriate curve-fitting and data analysis software, interpret ...
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred qualifications, capabilities, and skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred qualifications, capabilities, and skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred qualifications, capabilities, and skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred qualifications, capabilities, and skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred Qualifications, Capabilities, and Skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred Qualifications, Capabilities, and Skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred Qualifications, Capabilities, and Skills
Experience with experimentation (A/B testing), cohort analysis, key performance indicators (KPIs ... executive and nontechnical audiences. Preferred Qualifications, Capabilities, and Skills
Work with product managers, data scientists, ML engineers, and other stakeholders to understand ... Proficiency in programming languages like Python for model development, experimentation, and ...
Work with product managers, data scientists, ML engineers, and other stakeholders to understand ... Proficiency in programming languages like Python for model development, experimentation, and ...
Work with product managers, data scientists, ML engineers, and other stakeholders to understand ... Proficiency in programming languages like Python for model development, experimentation, and ...
Work with product managers, data scientists, ML engineers, and other stakeholders to understand ... Proficiency in programming languages like Python for model development, experimentation, and ...
Define and own the product strategy, roadmap, and vision for Databricks Model Experimentation ... Collaborate with data science, engineering, architecture, and compliance teams to embed governance ...
Define and own the product strategy, roadmap, and vision for Databricks Model Experimentation ... Collaborate with data science, engineering, architecture, and compliance teams to embed governance ...
Define and own the product strategy, roadmap, and vision for Databricks Model Experimentation ... Collaborate with data science, engineering, architecture, and compliance teams to embed governance ...
Define and own the product strategy, roadmap, and vision for Databricks Model Experimentation ... Collaborate with data science, engineering, architecture, and compliance teams to embed governance ...
Principal Investigator/Associate Director, Translational Biomarker Discovery Laboratory
Wilmington, DE · On-site
... scientific rigor, reproducibility, and high-quality data interpretation across all assays and experimental approaches. • Provide technical leadership and mentorship within the Translational ...
Principal Investigator/Associate Director, Translational Biomarker Discovery Laboratory
Wilmington, DE · On-site
... scientific rigor, reproducibility, and high-quality data interpretation across all assays and experimental approaches. • Provide technical leadership and mentorship within the Translational ...
Ensure scientific rigor, reproducibility, and highquality data interpretation across all assays and experimental approaches. * Provide technical leadership and mentorship within the Translational ...
Ensure scientific rigor, reproducibility, and highquality data interpretation across all assays and experimental approaches. * Provide technical leadership and mentorship within the Translational ...
Scientist (Enzymes)
Wilmington, DE · On-site
Experience with Design of Experiments (DOE) and advanced statistical data analysis * Exposure to ... Opportunity to work on-site in a global science-driven organization with real-world impact
Scientist (Enzymes)
Wilmington, DE · On-site
Experience with Design of Experiments (DOE) and advanced statistical data analysis * Exposure to ... Opportunity to work on-site in a global science-driven organization with real-world impact
Research/Sr. Research Investigator, Computational Chemistry
Wilmington, DE · On-site +1
$95.60K - $121.80K/yr
This role will work at the interface of computational and experimental sciences, partnering closely with medicinal chemists, structural biologists, and data scientists to accelerate target validation ...
Research/Sr. Research Investigator, Computational Chemistry
Wilmington, DE · On-site +1
$95.60K - $121.80K/yr
This role will work at the interface of computational and experimental sciences, partnering closely with medicinal chemists, structural biologists, and data scientists to accelerate target validation ...
Research/Sr. Research Investigator, Computational Chemistry
Wilmington, DE · On-site
$95.60K - $121.80K/yr
This role will work at the interface of computational and experimental sciences, partnering closely with medicinal chemists, structural biologists, and data scientists to accelerate target validation ...
Research/Sr. Research Investigator, Computational Chemistry
Wilmington, DE · On-site
$95.60K - $121.80K/yr
This role will work at the interface of computational and experimental sciences, partnering closely with medicinal chemists, structural biologists, and data scientists to accelerate target validation ...
Research Scientist - Synthesis Development
$100K - $115K/yr
Job Summary: The Research Scientist - Synthesis Development will be part of the Enabling ... data analytic tools, including machine learning, design of experiments, automated laboratory ...
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Research Scientist - Synthesis Development
$100K - $115K/yr
Job Summary: The Research Scientist - Synthesis Development will be part of the Enabling ... data analytic tools, including machine learning, design of experiments, automated laboratory ...
Polymer Scientist
$93.53K - $137.18K/yr
Analyze and interpret experimental data; communicate insights to technical and business ... Publish research findings in scientific journals and present at conferences and professional forums
Polymer Scientist
$93.53K - $137.18K/yr
Analyze and interpret experimental data; communicate insights to technical and business ... Publish research findings in scientific journals and present at conferences and professional forums
Polymer Scientist
$93.53K - $137.18K/yr
Analyze and interpret experimental data; communicate insights to technical and business ... Publish research findings in scientific journals and present at conferences and professional forums
Polymer Scientist
$93.53K - $137.18K/yr
Analyze and interpret experimental data; communicate insights to technical and business ... Publish research findings in scientific journals and present at conferences and professional forums
Polymer Scientist
Wilmington, DE · On-site
$93.53K - $137.18K/yr
Analyze and interpret experimental data; communicate insights to technical and business ... Publish research findings in scientific journals and present at conferences and professional forums
Polymer Scientist
Wilmington, DE · On-site
$93.53K - $137.18K/yr
Analyze and interpret experimental data; communicate insights to technical and business ... Publish research findings in scientific journals and present at conferences and professional forums
You are responsible for the entire data lifecycle-from raw ingestion to executive-level insights ... Bachelor's degree from an accredited college or university in Computer Science, Data Science ...
You are responsible for the entire data lifecycle-from raw ingestion to executive-level insights ... Bachelor's degree from an accredited college or university in Computer Science, Data Science ...
Executive Data Scientist Experimentation information
What are the key skills and qualifications needed to thrive as an Executive Data Scientist Experimentation, and why are they important?
To thrive as an Executive Data Scientist Experimentation, you need advanced expertise in statistics, experimental design, and data modeling, typically backed by a PhD or master's degree in a quantitative field. Mastery of tools such as Python, R, SQL, and platforms like AWS or Azure, along with experience in A/B testing and big data systems, is essential. Leadership, strategic thinking, and strong communication skills are crucial for guiding teams and translating complex data into actionable business insights. These skills and qualities are vital for driving data-driven decision-making and delivering impactful business results through rigorous experimentation.
How does an Executive Data Scientist specializing in experimentation typically collaborate with cross-functional teams to drive business impact?
As an Executive Data Scientist focusing on experimentation, you will frequently partner with product managers, engineers, and business leaders to design and interpret experiments that inform strategic decisions. Your role involves translating business questions into measurable hypotheses, guiding teams on best practices for A/B testing, and ensuring rigorous analysis. Effective communication is key, as you'll need to present complex findings in a clear way that supports decision-making across the organization. This collaborative approach not only maximizes the impact of your data insights but also fosters a culture of evidence-based innovation.
What is an Executive Data Scientist Experimentation?
An Executive Data Scientist Experimentation is a senior-level professional who leads and oversees the design, implementation, and analysis of experiments and data-driven initiatives within an organization. They are responsible for developing experimentation strategies, guiding teams in A/B testing, and ensuring that data insights drive business decisions. This role often collaborates with executive leadership to align data science projects with strategic goals and maximize business impact. Executive Data Scientists also mentor junior staff, set best practices, and ensure that experimentation methods are rigorous and ethical.
What is the difference between Executive Data Scientist Experimentation vs Data Scientist Experimentation?
| Aspect | Executive Data Scientist Experimentation | Data Scientist Experimentation |
|---|---|---|
| Credentials | Advanced degrees (Master's/PhD), leadership experience | Bachelor's or Master's in Data Science, Statistics, or related fields |
| Work Environment | Strategic planning, cross-department collaboration, leadership roles | Data analysis, model development, experimentation execution |
| Employer & Industry Usage | Tech companies, finance, consulting firms with strategic focus | Tech, e-commerce, healthcare, and other data-driven industries |
Executive Data Scientist Experimentation roles focus on strategic oversight, leadership, and aligning experimentation efforts with business goals. Data Scientist Experimentation roles are more hands-on, involving designing and executing experiments to analyze data and inform decisions. Both roles require strong analytical skills, but the executive level emphasizes leadership and strategic impact.
What are the most commonly searched types of Data Scientist Experimentation jobs in Delaware? The most popular types of Data Scientist Experimentation jobs in Delaware are:
What are popular job titles related to Executive Data Scientist Experimentation jobs in Delaware? For Executive Data Scientist Experimentation jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Executive Data Scientist Experimentation jobs in Delaware look for? The top searched job categories for Executive Data Scientist Experimentation jobs in Delaware are:
What cities in Delaware are hiring for Executive Data Scientist Experimentation jobs? Cities in Delaware with the most Executive Data Scientist Experimentation job openings:
Full-time
Posted 14 days ago
Job description
Job Summary:
JPMorgan Chase is one of the oldest financial institutions, providing innovative financial solutions to a diverse clientele. The Applied AI/ML Lead will drive machine learning and generative AI projects, working collaboratively with product managers and engineers to implement cutting-edge AI solutions that enhance the Home Lending sector.
Responsibilities:
• Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
• Design, develop, and deploy state-of-the-art AI/ML/GenAI solutions to meet business objectives.
• Architect and implement robust, cloud-native MLOps/LLMOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production.
• Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products.
• Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems.
• Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
• Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML capabilities and results to both technical and non-technical audiences.
• Build AI Agents and chatbot
• Stay informed about the latest trends and advancements in the latest AI/ML research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
Qualifications:
Required:
• Bachelor’s degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
• 5+ years of experience in Machine Learning and Artificial Intelligence engineering.
• Experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Extensive hands-on technical experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, AWS Bedrock, Transformers, LangChain/LngGraph.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), orchestration tools (Airflow, FastAPI, etc.) and architectural design, implementation, and performance optimization.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, deep learning, reinforcement learning), and generative model architectures.
• Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
Preferred:
• Familiarity with the financial services industries.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
• Familiarity with ethical AI, including bias mitigation, explainability and escalation protocols for risky outputs.
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.
JPMorgan Chase is one of the oldest financial institutions, providing innovative financial solutions to a diverse clientele. The Applied AI/ML Lead will drive machine learning and generative AI projects, working collaboratively with product managers and engineers to implement cutting-edge AI solutions that enhance the Home Lending sector.
Responsibilities:
• Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
• Design, develop, and deploy state-of-the-art AI/ML/GenAI solutions to meet business objectives.
• Architect and implement robust, cloud-native MLOps/LLMOps pipelines and distributed AI/ML infrastructure (AWS, Azure, GCP) for scalable, efficient deployment and monitoring of models in production.
• Direct the development and deployment of advanced generative AI solutions (LLMs, RAG, NLP, AI Agents) and classical ML models, integrating state-of-the-art techniques into the ML platform to create innovative fintech products.
• Develop advanced monitoring and management tools to ensure high reliability and scalability of AI/ML systems.
• Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
• Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML capabilities and results to both technical and non-technical audiences.
• Build AI Agents and chatbot
• Stay informed about the latest trends and advancements in the latest AI/ML research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
Qualifications:
Required:
• Bachelor’s degree or MS or PhD in quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science.
• 5+ years of experience in Machine Learning and Artificial Intelligence engineering.
• Experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Extensive hands-on technical experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, AWS Bedrock, Transformers, LangChain/LngGraph.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), orchestration tools (Airflow, FastAPI, etc.) and architectural design, implementation, and performance optimization.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, deep learning, reinforcement learning), and generative model architectures.
• Expert in Large Language models (OpenAI, Anthropic, Mistral, etc) including fine-tuning models, prompt engineering, embeddings and context window.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
Preferred:
• Familiarity with the financial services industries.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
• Familiarity with ethical AI, including bias mitigation, explainability and escalation protocols for risky outputs.
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.