4,808 Big Data Platforms jobs in the United States

About Profound

Profound is an NYC-based AI startup helping brands measure and improve their visibility in AI platforms such as ChatGPT. We partner with some of the biggest brands and marketing agencies, including companies like MongoDB, Indeed, Mercury, DocuSign, Zapier, Ramp, Rho, Golin, Workable, Mejuri, Eight Sleep, G2, US Bank, Chime, and Clay.

We recently raised a $35 million Series B funding round led by Sequoia Capital, with continued backing from venture capital firms Kleiner Perkins, Khosla Ventures, Saga VC, and South Park Commons, as well as angel investors including Guillermo Rauch (Vercel) and Andrew Karam (Applovin).

Learn more at tryprofound.com.

Profound is on a mission to help companies understand and control their AI presence. As a Data Scientist , you'll map every human-AI interaction to help brands turn AIs into their strongest advocates. You'll build predictive models, develop sampling techniques, and optimize brand visibility in AI-driven search (e.g., ChatGPT, Perplexity). Your work will directly impact how businesses shape their presence in the generative AI era.

What You'll Do

• Develop and refine predictive models to analyze and forecast AI-driven search behavior.
• Design sampling and data classification techniques to improve AI-driven brand insights.
• Leverage LLMs/NLP to extract meaningful insights from unstructured text data.
• Work with large datasets, ensuring efficiency in querying, cleaning, and classification.
• Design and conduct A/B tests or other experimentation frameworks to measure impact.
• Collaborate with the founding team to turn complex data insights into actionable business strategies.

Who You Are

• 3+ years of advanced analytics experience in technology, marketing, or advertising.
• Proficient in Python, R, and SQL, with hands-on experience querying and analyzing large datasets.
• Expertise in data sampling techniques, including stratified sampling, bootstrapping, and extrapolation.
• Strong background in predictive modeling and applying ML techniques to estimate event frequency.
• Deep understanding of Large Language Models (LLMs), their limitations, and real-world applications.
• Passionate about staying on top of AI research, especially in multi-modal AI and LLM advancements.
• Comfortable in a fast-moving, high-performance startup environment.

This is an on-site role in our Union Square office-designed for builders who thrive on speed, iteration, and impact.

Position- Data Science
Duration-Contract
Location- Austin, TX~ Sunnyvale, CA

Jd
1. Experience in Machine Learning and Deep Learning, including regression, classification, neural network, and Natural Language Processing (NLP), LLM.
2. Extensive experience in TIME SERIES.
3. Extensive experience on Natural Language Processing (NLP) libraries such as Spacy, NLTK, flair, and sklearn-crfsuite.
4. Strong background in DNN, CNN, RNN(LSTM), GAN, and libraries to deploy these models, such as Sklearn, Keras, Pandas, and TensorFlow.
5. Experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems, and generating data visualizations using R, Python.
6. Experience with common data science toolkits and libraries, such as Pandas, NumPy, SciPy, Scikit-learn.
7. Experience with data exploration to find actionable insights and make Product Recommendations through Funnel Analyses, A/B testing, Churn analysis, User Segmentation, Retention Rate, and business KPIs.
Data Science, Python, TIME SERIES, NLP, LLM

Regards,
Pallavi Verma
Sr. Technical Recruiter | Syntricate Technologies Inc.
Direct : |
Email : | Web:

We're hiring! connect with us on LinkedIn nd visit our Jobs Portal

Minority Business Enterprise (MBE) Certified | E-Verified Corporation | Equal Employment Opportunity (EEO) Employer

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Position- Data Science
Duration-Contract
Location- Urbana, MD

JD
• Minimum 7 years of IT Experience• Minimum 2 years of experience in developing AI enabled solutions• Expert level competency in Python• Hands-on experience developing and deploying Machine Learning solutions• Good knowledge and experience in developing GenAI embedded solutions• Hands-on experience with AI cloud services is an added advantage Key Responsibilities:• Machine Learning based model building, validation, deployment, and monitoring• Developing MLOps solution for continuous development , deployment, and monitoring of solutions• Developing GenAI embedded solutions across various use cases• Rapid experimentation of GenAI use cases using Azure cloud AI and data services• Development and deployment of GenAI embedded solutions using open source solutions

Regards,
Pallavi Verm
Sr. Technical Recruiter | Syntricate Technologies Inc.
Direct : |
Email : | Web:

We're hiring! connect with us on LinkedIn nd visit our Jobs Portal

Minority Business Enterprise (MBE) Certified | E-Verified Corporation | Equal Employment Opportunity (EEO) Employer

This e-mail message may contain confidential or legally privileged information and is intended only for the use of the intended recipient(s). Any unauthorized disclosure, dissemination, distribution, copying or the taking of any action in reliance on the information herein is prohibited. Please notify the sender immediately by email if you have received this email by mistake and delete this e-mail from your system. You have received this email as we have your email address shared by you or from one of our data sources or from our member(s) or subscriber(s) list. If you do not want to receive any further emails or updates, please reply and request to unsubscribe .

Position- Data Science
Duration-Contract
Location- Cupertino, CA

JD

• Data Scientist with strong Statistical Fundamentals learning Python with Pandas and NumPy Experience Strong Visualization
• Experience Strong understanding of Data Science Cycle OOP
• Python with Scientific and mathematical Experience and state Experience Need
• Digital : Data Visualization, Python for Data Science, Object Oriented Programming, Statistics & Analytics

Regards,
Pallavi Verma
Sr. Technical Recruiter | Syntricate Technologies Inc.
Direct : |
Email : | Web:

We're hiring! connect with us on LinkedIn nd visit our Jobs Portal

Minority Business Enterprise (MBE) Certified | E-Verified Corporation | Equal Employment Opportunity (EEO) Employer

This e-mail message may contain confidential or legally privileged information and is intended only for the use of the intended recipient(s). Any unauthorized disclosure, dissemination, distribution, copying or the taking of any action in reliance on the information herein is prohibited. Please notify the sender immediately by email if you have received this email by mistake and delete this e-mail from your system. You have received this email as we have your email address shared by you or from one of our data sources or from our member(s) or subscriber(s) list. If you do not want to receive any further emails or updates, please reply and request to unsubscribe .

Job Description:

• The Data Science Engineering Analyst will play a pivotal role in analysing complex datasets, designing and implementing predictive models, and deriving actionable insights to drive business decisions. This position requires a combination of data engineering skills and data science expertise to ensure robust data pipelines and effective analytical solutions.

Responsibilities:

• Apply advanced statistical methods to large complex data sets to understand impact of abuse to the client ecosystem. Contribute strategy and development of new workflows against additional known vectors of abuse.

• Learn complex and technical concepts and systems and deliver meaningful results using them. Communicate highly technical results and methods clearly.

• Maintain, foster and promote quality by providing regular feedback metrics to the Global team. Manage technological solutions for streamlining quality assurance and produce scalable training solutions to emergent workflows.

• Perform deceptive/manipulated content and generative AI investigations using various data sources, identify product vulnerabilities and drive anti-abuse experiments to prevent abuse. Work with engineers and interact cross-functionally with stakeholders to improve workflows via process improvements, automation and anti-abuse system creation.

• Develop high quality training materials, create consensus and maintain communication for client with business stakeholders.

Experience:

• 3 years of experience in data management, metrics analysis, experiment design and automation.

• Experience with classification systems, ranking systems, or similar.

• Experience collecting, managing, and synthesizing large data sets and information from disparate sources, statistical modelling, data mining and data analysis.

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ( .

US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

**Job Description:**
+ The Data Science Engineering Analyst will play a pivotal role in analysing complex datasets, designing and implementing predictive models, and deriving actionable insights to drive business decisions. This position requires a combination of data engineering skills and data science expertise to ensure robust data pipelines and effective analytical solutions.
**Responsibilities:**
+ Apply advanced statistical methods to large complex data sets to understand impact of abuse to the client ecosystem. Contribute strategy and development of new workflows against additional known vectors of abuse.
+ Learn complex and technical concepts and systems and deliver meaningful results using them. Communicate highly technical results and methods clearly.
+ Maintain, foster and promote quality by providing regular feedback metrics to the Global team. Manage technological solutions for streamlining quality assurance and produce scalable training solutions to emergent workflows.
+ Perform deceptive/manipulated content and generative AI investigations using various data sources, identify product vulnerabilities and drive anti-abuse experiments to prevent abuse. Work with engineers and interact cross-functionally with stakeholders to improve workflows via process improvements, automation and anti-abuse system creation.
+ Develop high quality training materials, create consensus and maintain communication for client with business stakeholders.
**Experience:**
+ 3 years of experience in data management, metrics analysis, experiment design and automation.
+ Experience with classification systems, ranking systems, or similar.
+ Experience collecting, managing, and synthesizing large data sets and information from disparate sources, statistical modelling, data mining and data analysis.
US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ( .
US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Organization Overview
The newly-created Data Science Platform (DSP) supports and advances the research objectives of Rockefeller Universitys faculty and staff by providing training and consultative support in the field of data science especially in the areas of machine learning and artificial intelligence (ML/AI) and deep learning (DL).
Overview
Reporting to the Chief Information Officer, and working primarily with Faculty, Research Staff, Postdoctoral Fellows, and Graduate Students, the Director leads a team of seven (7) Machine Learning Engineers that identify and work closely with internal and external resources to determine how to most effectively support University researchers' needs for applying ML/AI and/or other quantitative approaches to new and existing data sets across a wide variety of disciplines, including structural biology, imaging, microscopy, "omics," neuroscience, immunology/virology, and the physical sciences. The position also includes leadership of the Fisher Center AI Platform, which seeks to apply AI/ML techniques to understand the causes of Alzheimer's disease, improve the care of people living with it, and find a cure.
Responsibilities
Responsibilities include, but are not limited to the following:
+ Consult on experimental design and best usage, with emphasis on best practices for proper analysis and reproducibility;
+ Recruit and manage Data Science Platform staff members;
+ Develop and lead training/classes in ML/AI fundamentals and techniques; adapt and evolve training to best serve the changing needs of the research community;
+ Identify, improve, and/or create appropriate training data sets for ML/AI projects;
+ Advise researchers and collaborators on method selection and implementation, as well as on how to direct research projects to ensure alignment with emerging advancements in deep learning;
+ Maintain awareness of advances in the field and their applicability to problems of interest to members of Rockefeller's research community;
+ Identify and apply for appropriate grant funding opportunities;
+ Additional duties and special projects as assigned.
Qualifications
**REQUIRED QUALIFICATIONS:**
+ Ph.D. or equivalent degree in data science, machine learning, artificial intelligence, computer science, electrical engineering, statistics or a related field.
+ A minimum of ten (10) years of research experience in identifying, formulating and solving biological problems through the application of advanced artificial intelligence technologies.
+ At least two (2) years of leadership experience.
+ A strong publication record in top-tier venues focused on machine learning, artificial intelligence or their domain-specific applications, such as AAAI, NeurIPS, ICML, ICLR, IJCAI, KDD, ICCV, ECCV, CVPR, EMNLP, ACL, MICCAI, IJCV, TPAMI, TIP, ACM-MM, Nature, Nature Methods, Science and equivalent conferences and journals.
+ Broad knowledge on recent advances in artificial intelligence, such as foundation models (including large-language models, vision-language models, genomic foundation models, etc.), generative models, self-supervised learning, large-scale distributed training, efficient deep learning, with research expertise in at least one relevant field.
+ Basic knowledge of the deep learning tool stack, such as PyTorch, Python, CUDA, Linux, and computing cluster management.
+ Must possess excellent communication and interpersonal skills.
**PREFERRED QUALIFICATIONS:**
+ Prior work experience in a research related, academic environment is a plus.
The Rockefeller University is an equal opportunity employer - veterans/individuals with disabilities. Qualified applicants will receive consideration for employment without regard to characteristics protected by applicable local, state or federal law, including but not limited to disability and protected veteran status.
The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.
Compensation Range: Min
USD $175,000.00/Yr.
Compensation Range: Max
USD $190,000.00/Yr.

Manager Data Science

Manager , Data Scientist, Representation Learning for Customer Protection

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward 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 Retail Bank Customer Protection Data Science team has a relentless focus on innovation with a passion for improving customer experiences around fraud prevention. Detecting and preventing fraud behaviors as early as possible helps keep customer funds secure and enables the Bank to grow with confidence. Our team is constantly investing to improve and complement existing model-based defenses with the latest and greatest techniques from industry and academia. We often design features using SQL, python, and spark, and train models using a variety of python-centric modeling libraries. Data scientists often lead the deployment of these models in batch and event-based environments, and may additionally partner with engineering teams for deployments that interface with other real-time systems. The team is focused on giving our millions of customers comfort to know that their account is protected from attempts to take it over.

Role Description-

In this role, you will:

• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, Kubernetes, and more to build sequence models to detect fraud risk using deep learning techniques like transformers, LSTMs, and embeddings of tabular data

• Connect your deep technical modeling expertise to the pressing business goals of our fraud prevention strategy partners to create exciting solutions to demanding challenges

• Provide the engine to a research agenda with business opportunities at its heart

• Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses.

• Pilot machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

The Ideal Candidate is:

• 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.

• 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.

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date

• At least 2 years’ experience in open source programming languages for large scale data analysis

• At least 2 years’ experience with machine learning

• At least 2 years’ experience with relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

• At least 1 year of experience working with AWS

• At least 4 years’ experience in Python for large scale data analysis

• At least 4 years’ experience with machine learning and specifically deep learning sequence modeling architectures

• At least 4 years’ experience with SQL

Capital 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.

McLean, VA: $193,400 - $20,700 for Mgr, Data Science

Richmond, VA: 175,800 - 200,700 for Mgr, Data Science

Candidates 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 sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual 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 ; 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 or via email at . 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

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).

Manager Data Science

Manager , Data Scientist, Representation Learning for Customer Protection

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward 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 Retail Bank Customer Protection Data Science team has a relentless focus on innovation with a passion for improving customer experiences around fraud prevention. Detecting and preventing fraud behaviors as early as possible helps keep customer funds secure and enables the Bank to grow with confidence. Our team is constantly investing to improve and complement existing model-based defenses with the latest and greatest techniques from industry and academia. We often design features using SQL, python, and spark, and train models using a variety of python-centric modeling libraries. Data scientists often lead the deployment of these models in batch and event-based environments, and may additionally partner with engineering teams for deployments that interface with other real-time systems. The team is focused on giving our millions of customers comfort to know that their account is protected from attempts to take it over.

Role Description-

In this role, you will:

• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, Kubernetes, and more to build sequence models to detect fraud risk using deep learning techniques like transformers, LSTMs, and embeddings of tabular data

• Connect your deep technical modeling expertise to the pressing business goals of our fraud prevention strategy partners to create exciting solutions to demanding challenges

• Provide the engine to a research agenda with business opportunities at its heart

• Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading fraud defenses.

• Pilot machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

The Ideal Candidate is:

• 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.

• 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.

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date

• At least 2 years’ experience in open source programming languages for large scale data analysis

• At least 2 years’ experience with machine learning

• At least 2 years’ experience with relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

• At least 1 year of experience working with AWS

• At least 4 years’ experience in Python for large scale data analysis

• At least 4 years’ experience with machine learning and specifically deep learning sequence modeling architectures

• At least 4 years’ experience with SQL

Capital 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.

McLean, VA: $193,400 - $20,700 for Mgr, Data Science

Richmond, VA: 175,800 - 200,700 for Mgr, Data Science

Candidates 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 sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual 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 ; 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 or via email at . 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

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).