Top Principal Data Scientist Jobs in NYC

As a Principal Data Scientist at Capital One, you will partner with a cross-functional team to deliver data-driven insights and build machine learning models. You will leverage a broad stack of technologies and utilize your expertise in statistical analysis and machine learning to drive business goals.

Principal Data Scientist role at Capital One focusing on building machine learning models for US Card Acquisitions team. Responsibilities include partnering with cross-functional teams, leveraging technologies like Python and AWS, building machine learning models, and translating complex work into business goals. Ideal candidate is customer-first, innovative, creative, technical, statistically-minded, and a data guru.

Seeking a highly skilled Principal Data Scientist to perform and advise on technical analyses across various research areas related to healthcare data and analytics. Responsibilities include patient risk stratification, causal analysis, health economics analyses, financial modeling, and the development of analytical pipelines. Must function as an independent implementer of advanced quantitative research, review colleagues' work, advise company leadership, and collaborate with internal stakeholders.

Data Scientist role at Capital One focusing on experimentation and personalization using machine learning technologies. Responsibilities include building machine learning models, collaborating with cross-functional teams, and leveraging a variety of technologies to analyze large datasets.

Partner with cross-functional team to deliver AI powered products, leverage NLP expertise, build ML and NLP models, operationalize in production systems, and translate complexity into business goals.

Lead Data Scientist role at GoodRx focusing on consumer pricing, incentives & offers, and insurance. Responsible for leading data science projects, providing mentorship, and building forecasting and optimization systems.

As a Manager, Data Scientist at Capital One in the US Card Acquisitions team, you will lead the development of machine learning models for underwriting decisions in acquiring new credit card customers. You will collaborate with cross-functional teams, leverage a variety of technologies, build and deploy machine learning models, and translate technical complexity into business goals. The ideal candidate is customer-focused, innovative, creative, a leader, technically proficient, and statistically-minded.

Lead Data Scientist role at GoodRx focusing on data science projects related to consumer pricing, incentives, and insurance. Responsible for building forecasting and optimization systems that impact pricing strategies. Requires 6+ years of data science experience with a strong technical background in machine learning and model deployment.

As a Senior Data Scientist on The AI Training Team at Capital One, you will partner with a cross-functional team to deliver AI-powered products, leverage technologies to reveal insights within data, and translate complex work into tangible business goals. The ideal candidate is innovative, technical, statistically-minded, and a data guru. Basic qualifications include a Bachelor's/Master's/PhD degree plus 9/7/5 years of experience in data analytics, 4 years of experience in open source programming, machine learning, and relational databases.

As a Data Scientist, you will join our Data team to help us build and maintain strong analytic capabilities that will support Thyme Care’s mission.

The Principal Data Scientist will drive experimentation practices and analyses to enable trustworthy decisions at scale. They will have expertise in SQL, Python, Spark, AWS, and Databricks.

As a Data Scientist on the Growth Data Science team at Notion, you will collaborate with the Monetization team to accelerate self-serve revenue generation. Your responsibilities include analyzing user interactions with Notion, defining problems for influential projects, designing experiments to evaluate feature success, and influencing product roadmaps through data-driven insights.

The Senior Data Scientist NLP and GenAI role involves designing and implementing NLP algorithms, language models, and leading advanced analytics projects. Responsibilities include preprocessing textual data, training models for sentiment analysis, named entity recognition, and promoting ethical use of NLP technologies. Required qualifications include experience in NLP and expertise in machine learning techniques. Additional skills include leadership, problem-solving, and agile learning. The salary range for this position is $110,000 to $140,000 per year, eligible for short-term incentive compensation and comprehensive benefits at MetLife.

The Senior Data Scientist, Algorithms at Bowery builds production-facing data products to automate and optimize agricultural and operational functions across indoor vertical farms. Responsibilities include designing and implementing machine learning models, optimizing farm operations, and analyzing historical data for forecasting yields and growth potential.

Join the Cash App Support organization as a Data Scientist to analyze large datasets, derive valuable insights, drive meaningful change for customer interactions, and improve account issue resolutions. Partner with cross-functional teams, conduct A/B experiments, build data visualizations, and communicate findings effectively. Qualifications include a degree in statistics or data science with 5+ years of experience, proficiency in SQL and data visualization tools, and expertise in scripting languages like Python or R.

Looking for a Senior Data Scientist to join the Risk Data Science and Analytics Team at Square. Responsibilities include improving risk controls, managing core metrics, advising senior stakeholders, and building processes to identify high-risk activity. Key tasks involve fraud prevention, developing data pipelines, implementing machine learning solutions, and collaborating across various teams at Square.

Processing, cleansing, and analyzing data sets to extract insights using machine learning techniques. Collaborating with stakeholders to provide data-driven solutions. Enhancing data collection procedures and predicting future trends for proactive decision-making.