Data Domain Architect Lead
Wilmington, DE · On-site
... Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis • Partner with leads in Data Science ...
Data Domain Architect Lead
Wilmington, DE · On-site
... Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis • Partner with leads in Data Science ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
... data science techniques (e.g., Machine learning) * Superior written, oral communication and presentation skills with experience communicating concisely and effectively with all levels of management ...
Bachelor's degree in Data Science, Computer Science, Information Systems, Data Analytics, or a related field * 6+ years of experience in data management, data governance, risk management, analytics ...
Bachelor's degree in Data Science, Computer Science, Information Systems, Data Analytics, or a related field * 6+ years of experience in data management, data governance, risk management, analytics ...
Bachelor's degree in Data Science, Computer Science, Information Systems, Data Analytics, or a related field * 6+ years of experience in data management, data governance, risk management, analytics ...
Bachelor's degree in Data Science, Computer Science, Information Systems, Data Analytics, or a related field * 6+ years of experience in data management, data governance, risk management, analytics ...
Bachelor's degree in Data Science, Computer Science, Information Systems, Data Analytics, or a related field * 6+ years of experience in data management, data governance, risk management, analytics ...
Bachelor's degree in Data Science, Computer Science, Information Systems, Data Analytics, or a related field * 6+ years of experience in data management, data governance, risk management, analytics ...
PhD preferred. * 5+ years of experience in statistics, data science, decision science, or a related quantitative field. * 3+ years of experience building, reviewing, or validating machine learning ...
PhD preferred. * 5+ years of experience in statistics, data science, decision science, or a related quantitative field. * 3+ years of experience building, reviewing, or validating machine learning ...
PhD preferred. * 5+ years of experience in statistics, data science, decision science, or a related quantitative field. * 3+ years of experience building, reviewing, or validating machine learning ...
PhD preferred. * 5+ years of experience in statistics, data science, decision science, or a related quantitative field. * 3+ years of experience building, reviewing, or validating machine learning ...
Senior Data Marketing Specialist
$80K - $118K/yr
Maintain and enhance business procedures documentation and campaign management processes. * Research and apply emerging data science principles and techniques to inform business decisions.
Senior Data Marketing Specialist
$80K - $118K/yr
Maintain and enhance business procedures documentation and campaign management processes. * Research and apply emerging data science principles and techniques to inform business decisions.
Senior Data Marketing Specialist
Wilmington, DE · On-site
$80K - $118K/yr
Maintain and enhance business procedures documentation and campaign management processes. * Research and apply emerging data science principles and techniques to inform business decisions.
Senior Data Marketing Specialist
Wilmington, DE · On-site
$80K - $118K/yr
Maintain and enhance business procedures documentation and campaign management processes. * Research and apply emerging data science principles and techniques to inform business decisions.
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 ...
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 ...
Marketing Data Specialist
Wilmington, DE · On-site
$65K - $94K/yr
... management and marketing. * Other duties assigned. Minimum Qualifications: * Bachelor's Degree in Computational and Data Science, Economics, Statistics, or Math; or BS degree in other field in ...
Marketing Data Specialist
Wilmington, DE · On-site
$65K - $94K/yr
... management and marketing. * Other duties assigned. Minimum Qualifications: * Bachelor's Degree in Computational and Data Science, Economics, Statistics, or Math; or BS degree in other field in ...
Marketing Data Specialist
$65K - $94K/yr
... management and marketing. * Other duties assigned. Minimum Qualifications: * Bachelor's Degree in Computational and Data Science, Economics, Statistics, or Math; or BS degree in other field in ...
Marketing Data Specialist
$65K - $94K/yr
... management and marketing. * Other duties assigned. Minimum Qualifications: * Bachelor's Degree in Computational and Data Science, Economics, Statistics, or Math; or BS degree in other field in ...
... Loyalty Management, Forecasting Data Understanding of Sales, Inventory, Store, Product and ... Science, Engineering or Physics 7+ years applied experience devising, deploying and servicing ...
... Loyalty Management, Forecasting Data Understanding of Sales, Inventory, Store, Product and ... Science, Engineering or Physics 7+ years applied experience devising, deploying and servicing ...
Marketing Content Implementation Lead - AEM (Hybrid)
Wilmington, DE · On-site
$114K - $172K/yr
... Manager (AEM) to engage with new and existing customers/clients. By implementing AEM, the ... Operate in AEM daily to create content fragments, apply meta-data and support authors in building ...
Marketing Content Implementation Lead - AEM (Hybrid)
Wilmington, DE · On-site
$114K - $172K/yr
... Manager (AEM) to engage with new and existing customers/clients. By implementing AEM, the ... Operate in AEM daily to create content fragments, apply meta-data and support authors in building ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
Manager Meta Data Science information
What is the 80 20 rule in data science?
The 80/20 rule in data science suggests that roughly 80% of results come from 20% of the efforts or data. For a Manager of Data Science, understanding this principle helps prioritize features, models, or data sources that have the most significant impact on outcomes, enabling more efficient resource allocation and decision-making.
How much do meta data scientist managers make?
Meta Data Science Manager salaries typically range from $150,000 to $220,000 annually, depending on experience, location, and company size. They often receive additional compensation such as bonuses and stock options, and require strong leadership, technical skills, and experience managing data science teams.
What does a Manager of Meta Data Science do?
A Manager of Meta Data Science leads a team of data scientists in developing and implementing advanced analytics, machine learning models, and data-driven strategies for Meta (formerly Facebook). They are responsible for overseeing projects, mentoring team members, collaborating with cross-functional partners, and ensuring that data science solutions align with business goals. This role often requires both technical expertise and strong leadership skills to drive impactful decisions using data. Additionally, they work to improve processes, set research direction, and communicate findings to stakeholders.
How does a Manager Meta Data Science typically collaborate with cross-functional teams, and what communication challenges might arise?
A Manager Meta Data Science frequently collaborates with product managers, engineers, data analysts, and business stakeholders to ensure data-driven decision-making aligns with organizational goals. One common challenge is translating complex data science concepts into actionable business insights that are easily understood by non-technical teams. Effective communication and regular alignment meetings are essential to bridge knowledge gaps and ensure everyone is on the same page. Building strong relationships across departments and fostering a culture of transparency can help mitigate misunderstandings and streamline project delivery.
Can data scientists make $300k?
Data scientists, including those in managerial roles like Manager of Data Science, can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and in high-paying industries such as finance or technology. Achieving this level often requires a combination of technical expertise, leadership abilities, and sometimes stock options or bonuses.
Is 40 too late for data science?
For a Manager in Data Science, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering tools like Python or R and staying current with industry trends, regardless of age.
What are the key skills and qualifications needed to thrive as a Manager Meta Data Science, and why are they important?
To thrive as a Manager Meta Data Science, you need strong expertise in data science, machine learning, statistical analysis, and a relevant advanced degree, often in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, data visualization tools, and cloud-based platforms, as well as experience with big data frameworks, are typically required. Leadership, strategic thinking, and effective communication are crucial soft skills that enable success in managing teams and collaborating across departments. These skills are important because they ensure the ability to lead complex projects, drive data-driven decision-making, and align analytics goals with organizational objectives.
What are the most commonly searched types of Meta Data Science jobs in Delaware? The most popular types of Meta Data Science jobs in Delaware are:
What are popular job titles related to Manager Meta Data Science jobs in Delaware? For Manager Meta Data Science jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Manager Meta Data Science jobs in Delaware look for? The top searched job categories for Manager Meta Data Science jobs in Delaware are:
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Full-time
Posted 19 days ago
Job description
Job Summary:
JPMorganChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. As a Data Domain Architect Lead, you will manage a team to develop machine learning solutions through data annotation, curation, and validation while collaborating with other teams to optimize training data for machine learning models.
Responsibilities:
• Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
• Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
• Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
• Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
• Actively contribute to the team’s continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group
Qualifications:
Required:
• 6+ years of related experience in development of machine learning solutions
• Familiar with industry annotation and labeling methods
• Experience with various data modeling techniques and tools
• Familiar with Finance and Banking products
• Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
• Excellent analytical and problem-solving skills and the ability to pay close attention to detail
• Experience using Python in working with and analyzing large real-world datasets
• Working knowledge of information and data retrieval
• Working knowledge of machine learning and artificial intelligence paradigms and libraries
• Familiar with Large Language Models (LLMs) and prompt engineering
Preferred:
• Masters or PhD in a related field, or Bachelors
• Technical understanding of common relational database systems; i.e., Teradata and Oracle
• Excellent command of the Structured Query Language (SQL)
• Knowledge of SAS or Scala, and Python languages
• Knowledge of Advanced Statistics
• Advanced analytical thinking and problem-solving skills
• Strong interpersonal & communication skills
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.
JPMorganChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. As a Data Domain Architect Lead, you will manage a team to develop machine learning solutions through data annotation, curation, and validation while collaborating with other teams to optimize training data for machine learning models.
Responsibilities:
• Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
• Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
• Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
• Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
• Actively contribute to the team’s continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group
Qualifications:
Required:
• 6+ years of related experience in development of machine learning solutions
• Familiar with industry annotation and labeling methods
• Experience with various data modeling techniques and tools
• Familiar with Finance and Banking products
• Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
• Excellent analytical and problem-solving skills and the ability to pay close attention to detail
• Experience using Python in working with and analyzing large real-world datasets
• Working knowledge of information and data retrieval
• Working knowledge of machine learning and artificial intelligence paradigms and libraries
• Familiar with Large Language Models (LLMs) and prompt engineering
Preferred:
• Masters or PhD in a related field, or Bachelors
• Technical understanding of common relational database systems; i.e., Teradata and Oracle
• Excellent command of the Structured Query Language (SQL)
• Knowledge of SAS or Scala, and Python languages
• Knowledge of Advanced Statistics
• Advanced analytical thinking and problem-solving skills
• Strong interpersonal & communication skills
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.