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Data Science Project Manager Jobs in New York (NOW HIRING)

Join our fast-growing Global Product Management Data Science team and help transform Gartner ... Lead data science projects in close collaboration with Data Engineering, Application development ...

They are seeking a Manager of Data Science to lead a team focused on core marketplace challenges, driving analytical strategy and improving decision-making across various business areas.

Data Science Manager

New York, NY · Remote

$70 - $100/hr

Data Science Experts Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on data science methodology ...

Data Analyst

Whitestone, NY · On-site

$75K - $90K/yr

You will have the opportunity to work on a variety of interesting data science projects that have ... Ability to multi-task and adjust priorities based on workload and direction from management * Self ...

You will have the opportunity to work on a variety of interesting data science projects that have ... Ability to multi-task and adjust priorities based on workload and direction from management * Self ...

VP Data Science As the VP of Data Science, you'll play a critical role in building a data-driven ... project management and organizational skills · Experience supporting and working with cross ...

Data Scientist II

New York, NY · Hybrid

$131K - $172K/yr

... better manage risk, build higher-performing provider networks, and create a standout consumer ... science projects across multiple teams and domains. In this role, you'll take ownership of ...

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Data Science Project Manager information

See New York salary details

$18

$62

$87

How much do data science project manager jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for data science project manager in New York is $62.92, according to ZipRecruiter salary data. Most workers in this role earn between $54.42 and $73.65 per hour, depending on experience, location, and employer.

What is the hottest job of the 21st century?

Data Science Project Managers are in high demand due to the rapid growth of data-driven decision-making across industries. They oversee data projects, coordinate teams, and require skills in analytics tools, project management, and communication. The role is considered one of the most sought-after careers in the 21st century for its impact and earning potential.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

Is 40 too late for data science?

For a Data Science Project Manager, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering tools like Python or R and understanding business needs, regardless of age.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior management positions. Achieving this level often requires a combination of technical expertise, certifications, and leadership responsibilities.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a Data Science Project Manager, and why are they important?

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

Can a data scientist become a project manager?

Yes, a data scientist can become a project manager by developing skills in leadership, communication, and project planning. Gaining experience in managing teams, understanding project workflows, and obtaining certifications like PMP can facilitate this transition.
What are popular job titles related to Data Science Project Manager jobs in New York? For Data Science Project Manager jobs in New York, the most frequently searched job titles are:
What cities in New York are hiring for Data Science Project Manager jobs? Cities in New York with the most Data Science Project Manager job openings:
Infographic showing various Data Science Project Manager job openings in New York as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $130,865 per year, or $62.9 per hour.
Senior Manager - Data Science

Senior Manager - Data Science

American Express

Manhattan, NY • On-site

$123K - $215K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 29 days ago


American Express rating

8.5

Company rating: 8.5 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

25th of 146 rated financial services


Job description


Global Commercial Services (GCS) is the global leader in providing payments solutions for Small, Medium, and Large Enterprises. We are in the business of helping our clients get business done! Accelerating sales and driving profitable charge volume growth are critical for the success of the organization. The Sales Enablement team is instrumental in driving these objectives.
The Senior Manager will play a critical role supporting the development of growth and data-driven strategies to improve Sales portfolio performance and drive execution, while working alongside senior leadership within GCS. The ideal candidate should demonstrate creativity, curiosity, and passion for dealing with large amounts of data and converting it into valuable, actionable information. We seek a thought-leader and a problem-solver who can blend business, technical, and industry best practices when it comes to developing data-driven solutions.
The position will provide consultative support to the GCS Sales leadership team through development of analytical solutions. The incumbent will highlight trends, risks, and opportunities to enhance business decision-making processes, while working very closely with Sales, Marketing, Finance, Technology, and Capabilities partners to drive Sales growth. The incumbent will lead a team of data scientists to design, develop, and test ML/AI-derived solutions that deliver higher client engagement and efficiency improvements. The role is positioned at a unique intersection of deepening analytics and informing business outcomes. This is a fast-paced environment requiring a mix of strong relationship skills, passion for applied data science, people leadership, and a singular focus on excellence.
Responsibilities
  • Lead Data Science Projects: Design, develop, and deploy predictive and explanatory analytical solutions that address critical business problems using machine learning, NLP, and generative AI. Strengthen forecasting, refine incentive plan designs, and identify gaming behaviors
  • Drive Analytics: Deliver high-impact analytics to inform strategy by developing actionable insights into Sales and client behavior. Introduce new approaches to transform complex behavioral data and influence decision-making across the organization
  • GenAI Analytics Use Case Development: Lead key workstreams in the design, development, and operationalization of a GenAI-enabled analytics solution that synthesizes internal performance and external competitive signals into actionable insights, with defined success metrics and ongoing monitoring
  • Develop Modeling Capabilities: Build and evaluate models using modern ML frameworks (e.g., TensorFlow, PyTorch), focusing on scalability, performance, and interpretability
  • People Leadership: Lead a team of high-performing data scientists
  • Collaborate Across Teams: Establish and maintain close relationships with key cross-functional stakeholders to understand business strategies, develop goals, and address opportunities
  • Develop Scalable Solutions: Architect and deploy robust, efficient, and scalable data pipelines and modeling solutions using modern cloud and distributed compute patterns
  • Lead Innovation Through External Perspective: Stay current on advancements in machine learning, deep learning, and generative AI; evaluate emerging approaches; translate theoretical advances into practical, scalable solutions that advance business outcomes. Challenge the status quo and demonstrate strong curiosity
  • Define Performance Indicators: Lead analytics and measurement across key performance indicators. Own stakeholder and executive-level communications on initiative progress, including automated monthly measurement tied to specific strategic initiatives
  • Communicate Insights Effectively: Present findings, recommendations, and results to both technical and non-technical audiences, including executive leadership, through clear reports, visualizations, and presentations, to enable data-driven decision-making

Qualifications
  • 4-5 years of relevant work experience
  • Bachelor's degree required, preferably in a quantitative field (e.g., Economics, Finance, Computer Science, Mathematics/ Statistics, Engineering)
  • Strong analytical and conceptual thinking acumen, with ability to translate complex, unstructured business problems into quantitative models. Leverage external insights and tools (from academia or other industries) where needed
  • Capable of articulating key findings to senior leadership and stakeholders, leveraging insights to influence business decisions
  • Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and experience applying algorithms to real-world business problems
  • High proficiency in Python/SQL is required; experience with Hadoop and Spark is a plus
  • Experience with data querying and distributed analytics tools (e.g., Hive, PySpark, BigQuery) is required
  • Experience in a Big Data environment, including data mining and data processing. Ability to address performance issues and to manipulate both structured and unstructured data
  • Demonstrable experience with data visualization and reporting tools (e.g., matplotlib, seaborn, Tableau)
  • Proficiency with industry-recognized ETL methods, processes and standards
  • Advanced knowledge of Microsoft Office Suite (Excel pivot tables, deck-writing)
  • Ability to work independently as well as collaboratively in a dynamic, cross-functional environment, with a strong attention to detail and passion for learning

Preferred Qualifications:
  • Masters/PhD in a quantitative field (Computer Science, Statistics, Econometrics, Mathematics, Physics, Operation Research, Engineering, etc.)
  • 2+ years' experience of applying machine learning techniques to real-world business problems, including exposure to production ML and/or GenAI (e.g., LLM prompting, RAG, evaluation)
  • Stakeholder management at the executive level
  • People leadership experience

Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.
About Us
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the Team
We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
  • Competitive base salaries
  • Bonus incentives
  • 6% Company Match on retirement savings plan
  • Free financial coaching and financial well-being support
  • Comprehensive medical, dental, vision, life insurance, and disability benefits
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
  • 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counseling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
US Job Seekers - Click to view the "Know Your Rights" poster. If the link does not work, you may access the poster by copying and pasting the following URL in a new browser window: https://www.eeoc.gov/poster.
The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

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