Data Science Jobs in New York: Apply Today

Due to its fast-growing population, job seekers interested in data science can find lucrative careers in New York City. Given the increasing importance of data analysis for various fields, including but not limited to finance, healthcare, and many more, organizations are eager to employ qualified personnel to manage large datasets. New York is undeniably one of the most significant cities in the world, and it embraces innovation and ideas within the technology industry.

Data science positions in New York encompass a wide range of positions—from data analysts whose job mainly solves quantitative problems to machine learning engineers who build innovative algorithms. It is a profession that requires a person to be able to work with the city’s cultural demographics today and adapt well to new changes and upcoming business environments in life. It is also important to understand trends and developments happening in the data science job market in order to advance in one’s career, or to support one’s organization.

If you are a data scientist or an aspiring one who recently joined the analytics circle, then New York City is the best option. In the firms of Wall Street and Silicon Alley’s newest companies, below are the organizations that are looking to hire for the future of the New York economy. Building a successful requires a blend of technical skills, problem-solving abilities, and domain expertise. For those willing to further advance in your data science profession, do not miss the chance to apply and be part of the data scientists that are paving the way for New York City and the world. 

Many individuals might have a dream to start their career in New York. Here is the list of the jobs to kick-start your life. Have a glance at them. 

Data reporter is currently opening with the Wall Street Journal, which is seeking skilled candidates to work with its data team. Many leading companies are hiring for, making it a prime destination for data scientists. This individual will be responsible for reporting and data analysis across longer-term enterprise projects and shorter-term coverage. The desired applicant should have a good passion for working on high-impact journalism, be result-oriented, proficient in news analysis and be able to bring out stories in the news that will engage our readers.

• The ideal candidate will contribute strong, aggressive writing for enterprise projects and other stories and exclusive data analysis for all projects.

• They work together with reporters, editors, and other visual journalists to develop compelling, data-driven content.

• It is often easier to pitch story ideas and share your research data findings.

• Gather advanced knowledge of key areas of WSJ focus, including financial and economic matters, as well as political happenings.

• Web scraping tools, big data, and data mining tools, programming languages skills, etc., need to be used in this process.

• Gain a deep understanding of Amex Offers, including merchants, cardmembers, and digital behaviors. They want to know what makes our customers tick in all applicable countries.

• To set the strategic tone, assess business needs, and provide thought leadership on analytical solutions. A successful data science career consists of not only technical knowledge, analysis, and quality but also expertise in the domain area. 

• Encourage anyone looking to continue to grow in their data science career to take advantage of the opportunity to apply and be among the selected data scientists changing New York City and the world.

• Build a strong partnership with GMNS Marketing, Consumer Marketing, and the Amex Offers product and technology teams. Establish principles for prioritization and manage an analytic engagement pipeline for a variety of customers. They are all about keeping things organized and on track.

• It has established the technical team responsible for creating and maintaining comprehensive reporting solutions that rely on data virtualization to ensure that data from independent databases, the university data warehouse, and third-party sources is both accessible and easily incorporated into the final reports.

• Engage actively with stakeholders, including subject matter experts and cross-functional teams. Understand their specific needs, challenges, and desired outcomes. Then, translate those business requirements into well-defined analytical problems using your domain knowledge and expertise in techniques.

• Create and implement interactive data visualizations and dashboards. These will showcase scholarly productivity metrics from various data sources, allowing for data-driven insights and decision-making. It’s all about making progress on the university’s strategic objectives.

• Gain a deep understanding of Amex Offers, including merchants, cardmembers, and digital behaviors. We want to know what makes our customers tick in all applicable countries.

• To set the strategic tone, assess business needs, and provide thought leadership on analytical solutions. Manage the entire process, from conceiving ideas to completing and presenting analyses.

• We’re all about consistency, so please contribute regularly to our existing GitHub repository, update our centralized project management tool, and collaborate efficiently with our global team.

• Coordinate the entire workflow, including brainstorming and developing concepts as well as finishing and sharing cohesive analyses.

• Develop a powerful relationship with GMNS, Consumer Marketing, and the Amex Offers product and technology groups.

• Include all appropriate and relevant stakeholders and focus on cooperation with internal subject matter experts and cross-functional teams. That will entail understanding their needs or their analysis and what they want out of it. Next, turn those business requirements into quantitative problems in which you specialize by applying your knowledge of various techniques in data analysis.

• Develop and deploy engaging data tools and larger displays. These will showcase scholarly productivity metrics from various data sources, allowing for data-driven insights and decision-making. It’s all about making progress on the university’s strategic objectives. The vibrant tech ecosystem fuels the demand for in New York.

• Develop robust and reliable machine learning algorithms to help solve strategic business challenges. 

• Apply modern machine learning techniques to structured and unstructured data. 

• Leverage a broad range of technologies — Python, Konda, Azure Databricks, Java, Spark, and more — to uncover insights hidden in large amounts of statistical and textual data. 

• Develop machine learning models at all stages of development, from design through training, evaluation, validation, and deployment. 

• Serve as a mentor and technical leader for junior

• Communicate model algorithms and results to senior leadership and business partners in R&D of new machine learning techniques and applications.

• Alongside supply chain managers, technical staff, and agricultural operations specialists, new quantitative solutions must be developed to promote indoor farming conditions. 

• Analysis, design, and application of machine learning and usability analytics models. Execute SQL to transform the raw data generated by the farm into a comprehensive data warehouse as an authoritative source of all facts about the project. 

• Collaborate with other areas of practice to develop metrics, understand research requirements, and interpret results relevant to our products and business. 

• Build and use statistical, algorithmic models to actively surface and predict relationships in data. Analyze historical data on crop growth and environmental characteristics to model and predict yields for future crops and unlock insights into potential improvements.