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Statistics Data Science Jobs in New York (NOW HIRING)

Required : • 2+ years of data science experience in advertising, marketing, or related fields • Deep theoretical and practical understanding of statistical/ML techniques and experimental design ...

Data Analyst

Whitestone, NY · On-site

$75K - $90K/yr

Bachelor's Degree or higher in Analytics / Statistics / Data Science or other related subjects * Strong working knowledge of utilizing standard MS Office tools (Excel, Word, and Power Point)

Bachelor's Degree or higher in Analytics / Statistics / Data Science or other related subjects * Strong working knowledge of utilizing standard MS Office tools (Excel, Word, and Power Point)

S. and Prague to deliver scalable solutions Required Experience & Skills Bachelor's degree in mathematics, statistics, data science, computer science, or related field Advanced degree (PhD or Master ...

Bachelor's degree in mathematics, statistics, data science, computer science, or related field * Advanced degree (PhD or Master's + 3+ years industry experience) preferred * Hands-on experience with ...

Data Science Tutor

Elizabeth, NJ · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

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Statistics Data Science information

See New York salary details

$50.3K

$180.5K

$266.4K

How much do statistics data science jobs pay per year?

As of Jul 27, 2026, the average yearly pay for statistics data science in New York is $180,535.00, according to ZipRecruiter salary data. Most workers in this role earn between $146,100.00 and $186,000.00 per year, depending on experience, location, and employer.

Can I get a data science job with a statistics degree?

A statistics degree can provide a strong foundation for a data science role, as it covers essential skills like data analysis, probability, and statistical modeling. However, proficiency in programming languages such as Python or R, experience with data manipulation tools, and knowledge of machine learning are often required to qualify for data science positions.

What are the key skills and qualifications needed to thrive as a Statistics Data Scientist, and why are they important?

To thrive as a Statistics Data Scientist, you need a solid background in statistics, mathematics, and programming, often supported by a degree in a quantitative field. Proficiency with statistical software (such as R or SAS), programming languages (like Python), and data visualization tools is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and conveying insights to stakeholders. These competencies ensure accurate data analysis, actionable business solutions, and clear communication within cross-functional teams.

What are statistics data scientists?

Statistics data scientists are professionals who apply statistical methods and data analysis techniques to extract insights from large and complex datasets. They combine expertise in mathematics, computer science, and domain knowledge to solve real-world problems, build predictive models, and inform decision-making processes. Their work often involves collecting, cleaning, and analyzing data, as well as communicating findings to stakeholders through reports and visualizations.

Is statistics and data science a good career?

Statistics and data science are considered strong career options due to high demand across industries such as technology, finance, and healthcare. These roles typically require skills in programming, data analysis, and machine learning, and often offer competitive salaries and growth opportunities.

Is AI replacing statisticians?

AI is transforming the role of statisticians by automating routine data analysis tasks and enabling more complex modeling. However, statisticians are still essential for designing experiments, interpreting results, and ensuring data quality, making their skills valuable alongside AI tools in data science and analytics environments.

What are statistics and data science jobs?

Statistics and data science jobs involve analyzing data to extract insights, build models, and support decision-making. These roles often require skills in programming languages like Python or R, statistical methods, and data visualization tools. Professionals in these fields work in various industries such as finance, healthcare, and technology to solve complex problems using data-driven approaches.

How do Statistics Data Scientists typically collaborate with cross-functional teams to deliver impactful insights?

Statistics Data Scientists frequently work alongside professionals from engineering, product management, and business teams to define project goals and identify key metrics. Collaboration often includes translating complex statistical analyses into actionable business recommendations and clearly communicating findings to non-technical stakeholders. This role requires strong interpersonal skills, as well as the ability to adapt technical language for diverse audiences. Regular meetings, data review sessions, and shared project management tools are common parts of the workflow, ensuring that insights are aligned with organizational objectives.
What are popular job titles related to Statistics Data Science jobs in New York? For Statistics Data Science jobs in New York, the most frequently searched job titles are:
Infographic showing various Statistics Data Science job openings in New York as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $180,535 per year, or $86.8 per hour.
Manager, Data Science

Manager, Data Science

Spark Foundry

Manhattan, NY • On-site

Full-time

Posted 16 days ago


Job description

Job Summary:
Spark Foundry is one of the world’s most successful advertising agencies, leveraging identity, commerce, and artificial intelligence to connect brands with people. The Manager of Data Science will lead advanced audience development and data science solutions to drive client growth, working hands-on with large datasets and collaborating across teams to deliver actionable insights.
Responsibilities:
• Navigate a complex, multi-source data environment and creatively identify appropriate datasets and methodologies for ever-changing client questions
• Monitor data quality and maintain data science pipelines for client data assets, including 1PD and 3PD
• Develop, deploy, and maintain ML and AI workflows for identifying and targeting relevant audiences, including propensity/classification models as well as unsupervised clustering/segmentation
• Develop and execute novel methods of analyzing audiences, such as customer profiling, customer journeys, purchase predictions/recommendations, etc.
• Collaborate with strategy teams to translate technical outputs into relevant business insights and recommendations, including client-facing discussions and dashboards
• Collaborate with analytics teams to develop and implement testing frameworks for closed-loop audience measurement
• Develop and implement a test-and-learn roadmap to continuously refine data-driven strategies, enabling rapid optimization
• Contribute to data science team- and practice-building initiatives, e.g. presenting case studies in cross-functional forums, creating collateral around data capabilities, and pursuing internal research projects
• Document and share optimized, reusable code with data science colleagues using Git
• Continuously innovate, staying current with the latest technological developments and applying them to current workflows
• Independently set, communicate, and deliver against realistic expectations and timelines
• Guide the development of client data strategy and promote the adoption of data-driven processes across planning, activation, and measurement
• Proactively identify and pursue new use cases and opportunities to use data science capabilities to solve client challenges
Qualifications:
Required:
• 2+ years of data science experience in advertising, marketing, or related fields
• Deep theoretical and practical understanding of statistical/ML techniques and experimental design
• Hands-on experience with granular, disaggregated data, particularly behavioral consumer datasets and/or media logs
• Advanced proficiency with SQL for big data analytics
• Python for production-ready workflow development
• Experience with Databricks or similar cloud-based big data platforms, e.g. Snowflake, BigQuery, Redshift
• Experience building agentic workflows and integrating AI solutions into existing data and tech stacks
Preferred:
• Agency experience preferred
• Advanced degree in Statistics, Data Science, or other quantitative fields preferred
• Engagement with publisher walled gardens (AMC, ADH, etc.) a plus
Company:
Spark Foundry is one of six global media agency brands within Publicis Media. Founded in 2016, the company is headquartered in New York, USA, with a team of 1001-5000 employees. The company is currently Late Stage.