Physical therapist | Far Rockaway, NY

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:89157PDN-9977c3ef-cec6-4f14-ac16-cd743666fae7

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

a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description The US Card Acquisitions Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions of a new

credit card customer. We collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation.

We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter. In this role, you will: Partner with a cross-functional team of data

scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first.

You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.

Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. A data guru. " Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: Currently has, or is in the process of obtaining a Bachelor's Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining Ph D, with an expectation that required degree will be obtained on or before the scheduled start date At least 1 year of experience in open source programming languages for large scale data analysis At least 1 year of experience with machine learning At least 1 year of experience with relational databases Preferred Qualifications: Master's Degree in " STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or Ph D in " STEM" field (Science, Technology, Engineering, or Mathematics)At least 1 year of experience working with AWSAt least 3 years' experience in Python, Scala, or RAt least 3 years' experience with machine learning At least 3 years' experience with SQLCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting.

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $161,900 - $184,800 for Data Science Ph DCandidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please.

Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to interaction (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, interactionual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace.

Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at -xyz X or via email at xyz X@.

All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to xyz X@ Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities.

Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). PDN-9abf9a16-5f34-450d-899a-0999c979d100