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Data Science And Analytics Jobs in New York (NOW HIRING)

Your Skills And Experience * 5+ years of experience in data science, analytics, or applied machine learning, ideally in operational, process, or productadjacent environments. * Bachelor's, Master ...

Data Scientist, GTM

Manhattan, NY · On-site

$275 - $370/hr

About the Role As part of our growing Data Science & Analytics team, you will play an instrumental role in Anthropic's mission of building safe and beneficial AI--this time by driving data‑informed ...

Deliver analytics, reporting and insight initiatives that inform strategic planning and performance ... Bachelor's degree in Statistics, Mathematics, Data Science, Data Analytics, Business Intelligence ...

Your Skills And Experience * 5+ years of experience in data science, analytics, or applied machine learning, ideally in operational, process, or product-adjacent environments. * Bachelor's, Master ...

Analytics, Insights, & Artificial Intelligence ATTENTION: This role is not eligible for TD work ... The Senior Manager, Data Science leads a specialized team of data professionals varying in size and ...

Showing results 41-60

Data Science And Analytics information

See New York salary details

$41K

$134.3K

$215K

How much do data science and analytics jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data science and analytics in New York is $134,280.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,800.00 and $148,800.00 per year, depending on experience, location, and employer.

What is data science and analytics?

Data Science and Analytics refer to the fields that focus on extracting meaningful insights from large and complex data sets. Data Science combines statistics, computer science, and domain knowledge to analyze data, build predictive models, and support data-driven decision-making. Analytics, which is a core part of data science, involves examining data to discover trends, patterns, and correlations that can help organizations solve problems or improve processes. Professionals in these fields use tools such as Python, R, SQL, and machine learning algorithms to analyze data and communicate findings to stakeholders.

What are some common challenges faced by data science and analytics professionals when working with cross-functional teams?

Data science and analytics professionals often collaborate with colleagues from diverse backgrounds such as engineering, marketing, and business operations. One common challenge is translating complex analytical findings into actionable insights that non-technical stakeholders can easily understand. Additionally, aligning project objectives and timelines across teams can require strong communication and project management skills. Overcoming these challenges is essential for ensuring that data-driven solutions are effectively implemented and contribute to organizational goals.

What are the key skills and qualifications needed to thrive as a data science and analytics professional, and why are they important?

To thrive in Data Science and Analytics, you need strong skills in statistics, data manipulation, and programming, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools like Python, R, SQL, and data visualization platforms such as Tableau, along with knowledge of machine learning frameworks, is highly valued. Strong problem-solving ability, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills are crucial for turning raw data into strategic decisions that drive organizational success.

What is the difference between Data Science And Analytics vs Data Analysis?

AspectData Science And AnalyticsData Analysis
Required SkillsStatistical modeling, programming, machine learningData cleaning, descriptive statistics, visualization
Work EnvironmentCross-functional teams, R&D, predictive modelingBusiness reporting, dashboards, ad hoc analysis
Tools & TechnologiesPython, R, SQL, Hadoop, SparkExcel, SQL, Tableau, Power BI
Industry UsageTech, finance, healthcare, marketingRetail, finance, healthcare, operations

Data Science And Analytics involves advanced techniques like machine learning and predictive modeling, often requiring programming skills. Data Analysis focuses on interpreting existing data through descriptive statistics and visualization for decision-making. Both roles are essential but differ in complexity and scope.

What can I do with data science and analytics?

Data science and analytics professionals analyze large datasets to extract insights, support decision-making, and improve business processes. They use tools like Python, R, and SQL, and often work in environments that require strong statistical and programming skills. These roles can lead to careers in industries such as finance, healthcare, marketing, and technology, with opportunities for advancement and specialization.

What jobs can I get with a data science and analytics degree?

A degree in data science and analytics can lead to roles such as data analyst, data scientist, business intelligence analyst, machine learning engineer, and data engineer. These positions typically require skills in programming languages like Python or R, data visualization tools, and statistical analysis, often with certifications or experience in big data platforms and SQL. Job responsibilities include interpreting complex data, building predictive models, and supporting data-driven decision-making.

What cities in New York are hiring for Data Science And Analytics jobs?

Cities in New York with the most Data Science And Analytics job openings:

Infographic showing various Data Science And Analytics job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $134,280 per year, or $64.6 per hour.

Lead Data Scientist, Newsroom Analytics

The Wall Street Journal

New York, NY

Full-time

Medical, Retirement

Re-posted 22 days ago


Job description

Job Description:

The Wall Street Journal is seeking a Lead Data Scientist, Newsroom Analytics to drive our newsroom's audience-data strategy. Reporting to the Senior Manager, Newsroom Data, you will be embedded in one of the world's most influential newsrooms, working directly with newsroom coverage, audience, and product strategy teams on the decisions that shape how news is reported, prioritized, and delivered to millions of readers.

This is a highly autonomous and strategic role that demands both rigorous data science and sharp analytical instincts in equal measure. Working closely with editorial and audience leaders, you'll surface the right problems and own the full arc from solution design to adoption, building the metrics, models, and forecasts that teams rely on. This includes developing tools teams actually use, translating complex methodologies into clear recommendations, and consistently connecting your work to outcomes that matter: how readers discover, engage with, and return to WSJ journalism. Beyond your own output, you will serve as a technical anchor for the team, mentoring colleagues, establishing shared standards for analytical rigor, and proactively driving continuous improvements across our workflows. The ideal candidate seamlessly balances statistical rigor, strategic newsroom thinking, and a genuine investment in the people and practices around them.

This position will be based in our New York office.

You will:

  • Partner with our digital strategy, coverage and product teams to identify the highest-impact analytical opportunities, define the right questions, and shape the data science roadmap around problems that drive real newsroom outcomes.

  • Design and build predictive and explanatory models end-to-end, from feature engineering and validation through production, making principled tradeoffs between complexity and interpretability along the way.

  • Translate quantitative findings into clear, actionable recommendations for senior newsroom and business stakeholders, and partner with cross-functional teams to see those recommendations through to adoption.

  • Own the core metrics and measurement systems that newsroom teams rely on to evaluate performance and make editorial decisions, ensuring they are accurate, well-documented, and trusted.

  • Apply rigorous statistical thinking to measure real-world editorial and audience impact, drawing on causal inference and observational methods alongside controlled experimentation to isolate what's actually driving outcomes.

  • Mentor and develop junior data team members, establishing shared standards for rigorous, production-ready analysis and building the team's collective technical capability over time.


You have:

  • 5+ years of experience in data science, analytics, or applied machine learning, preferably in a media, publishing, or subscription-based environment.

  • Proven ability to own models end-to-end in a lean team setting, including scheduling, maintaining, and iterating on outputs using orchestration tools such as Airflow.

  • Strong proficiency in Python including feature engineering, model training, validation, and interpretation, with experience maintaining production-quality, reproducible code in Git.

  • Advanced SQL and hands-on experience with large-scale data warehouses (Snowflake/BigQuery) as well as ETL workflows/analytics engineering frameworks (dbt).

  • Experience applying causal inference and statistical methods to measure real-world outcomes from observational data.

  • Strong communication skills with the ability to frame quantitative findings as clear business or editorial recommendations for senior non-technical stakeholders, and a demonstrated ability to influence decisions without direct authority.

  • Experience building models that influence content strategy, audience development, or consumer retention.

Standout candidates will have strengths in one or more areas of the following:

  • Experience with NLP or text analysis methods, including topic modeling, classification, or entity extraction applied to content data.

  • Familiarity with off-platform attribution and audience measurement, specifically modeling the relationship between distributed content, platform referrals, and downstream subscription or engagement outcomes.

  • Experience leveraging AI to democratize data and enable faster time-to-insight.

To apply, please submit a resume and a cover letter explaining how your skills, experience and interests align with the expectations of the role by July 28th. Applications will be reviewed on a rolling basis, and we encourage early submission as the position may be filled before the deadline.

The Journal's reporters, editors, developers, and audio and visual journalists create important and impactful stories, firmly rooted in fact and adhering to the highest ethical standards. We report without fear or bias, and we maintain a proper sense of perspective, detachment and objectivity in our reporting.

*LI-JA1-WSJ

Reasonable accommodation: Dow Jones, Making Careers Newsworthy - All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status. EEO/AA/M/F/Disabled/Vets. Dow Jones is committed to providing reasonable accommodation for qualified individuals with disabilities, in our job application and/or interview process. If you need assistance or accommodation in completing your application, due to a disability, email us at talentresourceteam@dowjones.com. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates.

Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic under applicable law. EEO/Disabled/Vets

Reasonable Accommodation

We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process. If you need assistance or accommodation in completing your application or participating in an interview due to a disability, email us at talentresourceteam@dowjones.com. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates.

Please refer to the privacy notice at the bottom of this page for submitting any data access, deletion, or other data subject rights requests, where permitted under your local laws and regulations.

Business Area:

Dow Jones - News - WSJ

Job Category:

Data Analytics/Warehousing & Business Intelligence

Union Status:

Union roleBase Pay Range: $135,000 - $155,000

We're committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidate's experience, skills, location, and other relevant factors.

For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions.

For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees.