Science Jobs is an employment niche focused on job opportunities within the science sector. It encompasses a diverse range of positions from research and development, lab work, to academic and corporate roles in various scientific disciplines like biology, chemistry, physics, and environmental science. The key feature of Science Jobs is its specialized nature, catering to individuals with a strong background in science and a passion for research and innovation. It provides a platform for employers to find highly-skilled professionals and for job-seekers to find roles that match their expertise. Science Jobs often requires candidates to have a specific set of qualifications, including advanced degrees and relevant experience, thus ensuring a highly qualified workforce driving scientific progress.
Science Jobs refer to employment opportunities within the various fields of science, ranging from entry-level positions to advanced research and academic roles. Key features of these jobs often include conducting experiments, data analysis, problem-solving, and innovation in sectors like biology, chemistry, physics, and environmental science. Science Jobs demand a strong educational background and typically offer the potential for contributing to technological advancements and understanding of the natural world. These positions are pivotal in driving scientific progress and can be found in laboratories, universities, and industry settings.
Science jobs refer to employment opportunities within the fields of science, encompassing a wide range of disciplines such as chemistry, physics, biology, and environmental science, among others. These jobs are characterized by their focus on research, data analysis, and application of the scientific method to investigate natural phenomena or to develop new technologies. Individuals in science jobs often work in laboratories, universities, research institutions, or within the private sector. They are crucial for the advancement of knowledge, innovation, and the practical application of scientific discoveries to improve various aspects of life and solve complex problems.
Science Jobs refer to a broad category of careers focused on the pursuit of scientific research, practical applications of scientific knowledge, and the advancement of technology. These roles are typically found in sectors such as healthcare, engineering, environmental science, and pharmaceuticals. Key characteristics of Science Jobs include a strong emphasis on problem-solving, analytical skills, and a solid foundation in scientific principles. Individuals in these positions often engage in data analysis, experimentation, and innovation to contribute to scientific understanding and development. The field is dynamic and constantly evolving, offering a diverse range of opportunities for specialization and advancement.
Science Jobs refer to a broad category of careers focused on the pursuit of scientific research, practical applications of scientific knowledge, and the advancement of technology. These roles are typically found in sectors such as healthcare, engineering, environmental science, and pharmaceuticals. Key characteristics of Science Jobs include a strong emphasis on problem-solving, analytical skills, and a solid foundation in scientific principles. Individuals in these positions often engage in data analysis, experimentation, and innovation to contribute to scientific understanding and development. The field is dynamic and constantly evolving, offering a diverse range of opportunities for specialization and advancement.
Science Jobs refer to a broad category of careers focused on the pursuit of scientific research, practical applications of scientific knowledge, and the advancement of technology. These roles are typically found in sectors such as healthcare, engineering, environmental science, and pharmaceuticals. Key characteristics of Science Jobs include a strong emphasis on problem-solving, analytical skills, and a solid foundation in scientific principles. Individuals in these positions often engage in data analysis, experimentation, and innovation to contribute to scientific understanding and development. The field is dynamic and constantly evolving, offering a diverse range of opportunities for specialization and advancement.
Science Jobs is an employment niche focused on job opportunities within the science sector. It encompasses a diverse range of positions from research and development, lab work, to academic and corporate roles in various scientific disciplines like biology, chemistry, physics, and environmental science. The key feature of Science Jobs is its specialized nature, catering to individuals with a strong background in science and a passion for research and innovation. It provides a platform for employers to find highly-skilled professionals and for job-seekers to find roles that match their expertise. Science Jobs often requires candidates to have a specific set of qualifications, including advanced degrees and relevant experience, thus ensuring a highly qualified workforce driving scientific progress.
Science Jobs are career positions specifically within the wide domain of science, spanning across various disciplines including biology, chemistry, physics, and environmental science, among others. These jobs often feature a focus on research, development, innovation, and exploration. They can be found within academic institutions, private sector companies, research organizations, and government agencies. Characteristics of science jobs include a strong emphasis on analytical skills, problem-solving, critical thinking, and a commitment to continuous learning to keep pace with evolving scientific knowledge and technological advancements.
and professionally through various resources and programs. New York Life is a relationship-based company and appreciates how both virtual and in-person interactions support our culture. The Center for Data Science and Artificial Intelligence (CDSAi) is the 70-person innovative corporate Analytics group within New York Life.
l We are a rapidly growing entrepreneurial department which designs, creates, and offers innovative data-driven solutions for many parts of the enterprise. For more information on CDSAi, please visit our website ( /careers/corporate/data-science ). We have the freedom to explore external data sources and new statistical techniques and are excited about delivering a
whole new generation of predictive analytics and artificial intelligence solutions. In the 7 years of the existence of CDSAi we have built a lot of predictive modeling solutions that are being used by various areas in the company.
We have also stood up a modern model deployment platform that allows our models to be accessed in real time or batch (via APIs) from any production system in the company. In addition to several data science teams, CDSAi has a dedicated ML Ops team (for all infrastructure, data and model deployments), our own project management office, a model governance team, a development team (training, internships, media, events, other internal and external branding) and
data science product managers. This role will support our newly formed generative AI practice and report to the director of data science for generative AI.
The person in the role is expected to have prior experience with creating generative AI solutions for practical business use cases. NYL's CEO has expressed that he wants the company to be a leader in generative AI in our industry. Hence, this role has to opportunity to help build out that vision. Since not every data science project may require generative AI, expert-level familiarity with regular statistical predictive modeling methodologies and practice is also essential. Responsibilities Supports and helps build a generative AI practice within CDSAi.
This includes supporting use case development and associated stakeholder management in various business areas. It also means influencing infrastructure and tooling (in collaboration with ML Ops and IT), education of stakeholders and community, and governance (in collaboration with model governance team and Legal). Managing various stakeholders at the same level during solution design and project execution to successfully create solutions and deploy them into full production. Independently leads and contributes to data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support.
Demonstrates to internal and external stakeholders how analytics can be implemented to maximize business benefits. Provides technical support, which includes strategic consulting, needs backssments, project scoping and the preparation/presentation of analytical proposals. Utilizes advanced statistical/ AI techniques to create high-performing predictive models and other solutions to address business objectives and client needs.
Tests new statistical and machine learning analysis methods, software and data sources for continual improvement of quantitative solutions. Implements analytical models into production by collaborating with technology and ML Ops teams. Utilizes data visualization tools for model testing, modeling results and data patterns exhibition. Design performance metrics for model selection and performance monitoring. Utilizes data wrangling/data matching/ETL techniques while programming in several languages to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets.
Deploys analytical solution in production systems. Works closely with the business areas, IT, Legal, Government relations and several other groups in designing, building, and implementing these solutions. Evangelizes the use of data-based decision making and Analytics within New York Life. Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, with internal clients and stakeholders on project/test results, opportunities, questions.
Resolves problems and removes obstacles to timely and high-quality project completion. Works collaboratively with project and product managers within CDSAi and on other teams. Supports internal events, expos, lunch & learns, etc. with displays and presentations. Follows industry trends in insurance and related data/analytics processes and businesses. Functions as the analytics expert in meetings with other internal areas and external vendors. Contributes ideas and actively participates in proof-of-concept tests of new processes and technologies.
Stays up to date on existing and proposed legislation and regulation (on federal and state level) that impact AI in underwriting. Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects. Travels to events and vendor meetings as needed ( Required qualifications Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, or similar. 4+ years of experience with predictive analytics using large and complex datasets.
Substantial expertise in both parametric statistical modeling techniques (linear regression, GLM, survival analysis, time series, etc. ) and non-parametric techniques (GBM, NN, NLP). Expertise in regularization techniques (Ridge, Lasso, elastic nets), variable selection techniques, feature creation (transformation, binning, high level categorical reduction, etc. ), validation (holdouts, CV, bootstrap) and model performance measures (may need to create new ones). Substantial prior programming experience in languages such as R, Python, SPARK, SQL. Comfort with professional software development process and Git Hub.
Demonstrated expertise in deploying real-time models into production environments. This includes production-ready code, containerizing models, testing, and integration into business processes. Detailed recent NLP experience (basic techniques, large language models, transformers, etc. ) 2+ years of experience with generative AI solutions (both development and deployment/integration). Ideally this would include training, fine-tuning and prompt engineering. Experience with disparate impact testing vs. protected classes of statistical models is a plus.
Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is essential since you will have a lot of exposure to different internal groups (Business functions, Data, IT, Legal, Government Relations, etc. ) as well as third-party data vendors and consultants. Experience with insurance or consumer financial data is a plus. Location: 51 Madison Ave, Manhattan. Presence in the office is required Tuesday - Thursday. Salary range: $132,500-$197,500 Overtime eligible: Exempt Discretionary bonus eligible: Yes Sales bonus eligible: No Click here to learn more about our benefits.
Starting salary is dependent upon several factors including previous work experience, specific industry experience, and/or skills required. Recognized as one of Fortune's World's Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. We invite you to bring your talents to New York Life, so we can continue to help families and businesses " Be Good At Life.
" To learn more, please visit Linked In , our Newsroom and the Careers page of . Job Requisition ID: 89157 Nearest Major Market: Manhattan Nearest Secondary Market: New York City Job Segment: Testing, VP, Executive, Data Analyst, Scientific, Technology, Management, Data, Engineering Requisition #: 104303xyz X6ahf9io63
and professionally through various resources and programs. New York Life is a relationship-based company and appreciates how both virtual and in-person interactions support our culture. The Center for Data Science and Artificial Intelligence (CDSAi) is the 70-person innovative corporate Analytics group within New York Life.
l We are a rapidly growing entrepreneurial department which designs, creates, and offers innovative data-driven solutions for many parts of the enterprise. For more information on CDSAi, please visit our website ( /careers/corporate/data-science ). We have the freedom to explore external data sources and new statistical techniques and are excited about delivering a
whole new generation of predictive analytics and artificial intelligence solutions. In the 7 years of the existence of CDSAi we have built a lot of predictive modeling solutions that are being used by various areas in the company.
We have also stood up a modern model deployment platform that allows our models to be accessed in real time or batch (via APIs) from any production system in the company. In addition to several data science teams, CDSAi has a dedicated ML Ops team (for all infrastructure, data and model deployments), our own project management office, a model governance team, a development team (training, internships, media, events, other internal and external branding) and
data science product managers. This role will support our newly formed generative AI practice and report to the director of data science for generative AI.
The person in the role is expected to have prior experience with creating generative AI solutions for practical business use cases. NYL's CEO has expressed that he wants the company to be a leader in generative AI in our industry. Hence, this role has to opportunity to help build out that vision. Since not every data science project may require generative AI, expert-level familiarity with regular statistical predictive modeling methodologies and practice is also essential. Responsibilities Supports and helps build a generative AI practice within CDSAi.
This includes supporting use case development and associated stakeholder management in various business areas. It also means influencing infrastructure and tooling (in collaboration with ML Ops and IT), education of stakeholders and community, and governance (in collaboration with model governance team and Legal). Managing various stakeholders at the same level during solution design and project execution to successfully create solutions and deploy them into full production. Independently leads and contributes to data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support.
Demonstrates to internal and external stakeholders how analytics can be implemented to maximize business benefits. Provides technical support, which includes strategic consulting, needs backssments, project scoping and the preparation/presentation of analytical proposals. Utilizes advanced statistical/AI techniques to create high-performing predictive models and other solutions to address business objectives and client needs.
Tests new statistical and machine learning analysis methods, software and data sources for continual improvement of quantitative solutions. Implements analytical models into production by collaborating with technology and ML Ops teams. Utilizes data visualization tools for model testing, modeling results and data patterns exhibition. Design performance metrics for model selection and performance monitoring. Utilizes data wrangling/data matching/ETL techniques while programming in several languages to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets.
Deploys analytical solution in production systems. Works closely with the business areas, IT, Legal, Government relations and several other groups in designing, building, and implementing these solutions. Evangelizes the use of data-based decision making and Analytics within New York Life. Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, with internal clients and stakeholders on project/test results, opportunities, questions.
Resolves problems and removes obstacles to timely and high-quality project completion. Works collaboratively with project and product managers within CDSAi and on other teams. Supports internal events, expos, lunch & learns, etc. with displays and presentations. Follows industry trends in insurance and related data/analytics processes and businesses. Functions as the analytics expert in meetings with other internal areas and external vendors. Contributes ideas and actively participates in proof-of-concept tests of new processes and technologies.
Stays up to date on existing and proposed legislation and regulation (on federal and state level) that impact AI in underwriting. Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects. Travels to events and vendor meetings as needed ( Required qualifications Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, or similar. 4+ years of experience with predictive analytics using large and complex datasets.
Substantial expertise in both parametric statistical modeling techniques (linear regression, GLM, survival analysis, time series, etc. ) and non-parametric techniques (GBM, NN, NLP). Expertise in regularization techniques (Ridge, Lasso, elastic nets), variable selection techniques, feature creation (transformation, binning, high level categorical reduction, etc. ), validation (holdouts, CV, bootstrap) and model performance measures (may need to create new ones). Substantial prior programming experience in languages such as R, Python, SPARK, SQL. Comfort with professional software development process and Git Hub.
Demonstrated expertise in deploying real-time models into production environments. This includes production-ready code, containerizing models, testing, and integration into business processes. Detailed recent NLP experience (basic techniques, large language models, transformers, etc. ) 2+ years of experience with generative AI solutions (both development and deployment/integration). Ideally this would include training, fine-tuning and prompt engineering. Experience with disparate impact testing vs. protected classes of statistical models is a plus.
Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is essential since you will have a lot of exposure to different internal groups (Business functions, Data, IT, Legal, Government Relations, etc. ) as well as third-party data vendors and consultants. Experience with insurance or consumer financial data is a plus. Location:51 Madison Ave, Manhattan. Presence in the office is required Tuesday - Thursday. Salary range: $132,500-$197,500 Overtime eligible: Exempt Discretionary bonus eligible: Yes Sales bonus eligible: No Click here to learn more about our benefits.
Starting salary is dependent upon several factors including previous work experience, specific industry experience, and/or skills required. Recognized as one of Fortune's World's Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. We invite you to bring your talents to New York Life, so we can continue to help families and businesses " Be Good At Life.
" To learn more, please visit Linked In , our Newsroom and the Careers page of . Job Requisition ID:89157PDN-9977c3ef-cec6-4f14-ac16-cd743666fae7
Science Jobs are career positions specifically within the wide domain of science, spanning across various disciplines including biology, chemistry, physics, and environmental science, among others. These jobs often feature a focus on research, development, innovation, and exploration. They can be found within academic institutions, private sector companies, research organizations, and government agencies. Characteristics of science jobs include a strong emphasis on analytical skills, problem-solving, critical thinking, and a commitment to continuous learning to keep pace with evolving scientific knowledge and technological advancements.
