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Global Data Science Jobs (NOW HIRING)

PROPRIUS

Director Data Science

San Francisco, CA

Ability to define and implement a global Data Science strategy. * Proven track record in a Data Science leadership position. * Strong Machine Learning experience. * Ability to communicate effectively ...

Unilever

Data Science Manager

Hoboken, NJ · On-site

Data Science Manager Unilever is one of the world's leading suppliers of Food, Home, and Personal ... About Global Data & Technology (GDT) Data Foundation within GDT exists to make Unilever data ...

Lancesoft

Data Scientist

Santa Monica, CA · On-site

$80 - $100.72/hr

... Global Data & Digital Innovation (GDDI) organization within the pharmaceutical commercial domain. This role focuses on building data science and AI-driven solutions, including predictive patient ...

Visa

Manager, Data Production

Foster City, CA · Hybrid

You will work closely with engineering, data science, business intelligence, governance, security, and global business teams to ensure highquality, scalable, compliant, and highperforming data ...

Visa

Manager, Data Production

Foster City, CA · On-site

You will work closely with engineering, data science, business intelligence, governance, security, and global business teams to ensure high-quality, scalable, compliant, and high-performing data ...

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Global Data Science information

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$46K

$165K

$243.5K

How much do global data science jobs pay per year?

As of Jun 29, 2026, the average yearly pay for global data science in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Global Data Science vs Data Analyst?

AspectGlobal Data ScienceData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fields; often includes programming skillsBachelor's degree in Data Analysis, Statistics, or related fields; focus on analytical skills
Work EnvironmentGlobal teams, cross-cultural collaboration, advanced analytics projectsOffice or remote, focused on data reporting and visualization
Employer & Industry UsageTech companies, finance, healthcare, multinational corporationsRetail, marketing, finance, and smaller organizations

Global Data Science roles typically involve advanced analytics, machine learning, and working with international datasets, requiring broader technical skills. Data Analysts focus on interpreting data, creating reports, and supporting decision-making with less emphasis on complex modeling. Both roles are essential but differ in scope and complexity.

How does a Global Data Science role typically collaborate with teams across different regions and time zones?

In a Global Data Science role, collaboration often involves working with colleagues from various countries, which means navigating different time zones, cultures, and communication styles. Team members typically use collaborative platforms, regular virtual meetings, and clear documentation to ensure smooth workflow and knowledge sharing. Flexibility and proactive communication are key to managing project timelines and aligning on shared goals. This environment fosters learning from diverse perspectives and can lead to innovative solutions, but it also requires strong organizational and interpersonal skills.

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

To thrive as a Global Data Scientist, you need strong analytical skills, statistical knowledge, proficiency in programming (such as Python or R), and typically a degree in data science, computer science, or a related field. Experience with data visualization tools (like Tableau or Power BI), big data platforms (such as Hadoop or Spark), and relevant certifications (e.g., Google Data Analytics, AWS Certified Data Analytics) are often required. Excellent communication, problem-solving abilities, and cross-cultural collaboration skills help you stand out in international, cross-functional teams. These competencies are crucial for extracting actionable insights from complex global datasets and effectively driving business decisions across diverse markets.

What is Global Data Science?

Global Data Science is a field that involves analyzing and interpreting data from international sources to support decision-making on a worldwide scale. Professionals in this area use statistical methods, machine learning, and big data technologies to extract insights from diverse datasets that span multiple countries or regions. They often address complex challenges related to data integration, cultural differences, and varying regulatory environments. The goal is to provide actionable insights that can help multinational organizations optimize their operations, understand global trends, and create data-driven strategies.
More about Global Data Science jobs
What job categories do people searching Global Data Science jobs look for? The top searched job categories for Global Data Science jobs are:
Global Data Science jobs near you
Infographic showing various Global Data Science job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 64% Full Time, 26% Part Time, 7% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Global Data Science & AI Manager

Global Data Science & AI Manager

Harnham

The Woodlands, TX • On-site

Other

Posted 20 days ago

Job description

Global Data Science & AI Manager

Houston, TX (preferred) | Open to relocation

$150K-200K base + 10-20% bonus + equity (flexible)

About the Opportunity

We’re partnering with a global industrial manufacturing organization undergoing a major digital and AI transformation to hire their first dedicated Data Science & AI leader.

This is a net-new, highly visible role where you’ll be responsible for building AI capability from the ground up—defining strategy, identifying use cases, and delivering real business impact across a complex, global organization.

If you’re looking for a role where you can own something from day one and shape the future direction of a business, this is it.

What You’ll Be Doing

Own the AI Strategy

  • Assess current data, systems, and infrastructure
  • Define a clear AI and data roadmap aligned to business goals
  • Identify high-impact use cases across operations, product, and corporate functions

Drive Execution

  • Take AI/ML initiatives from concept through to production
  • Focus on real-world impact (efficiency, reliability, cost savings)
  • Balance quick wins with long-term transformation

Build from Scratch

  • Operate in a true greenfield environment
  • Work with messy, fragmented data and bring structure over time
  • Help shape future tooling, architecture, and best practices

Work Cross-Functionally

  • Partner with IT, R&D, engineering, and business leaders
  • Influence without direct authority
  • Drive adoption of data-driven decision making across the organization

Set the Foundation for Growth

  • Start as an individual contributor
  • Help define the long-term AI org structure
  • Play a key role in future hiring and team buildout

What We’re Looking For

Core Experience

  • 5–10 years in Data Science, AI/ML, or Advanced Analytics
  • Experience working in industrial, manufacturing, energy, or infrastructure-heavy environments
  • Proven ability to operate as both:
  • A strategic thinker (roadmap, prioritization)
  • A hands-on doer (execution, delivery)

Key Skills

  • Experience leading or contributing to data/AI transformation initiatives
  • Ability to translate business problems into technical solutions
  • Strong stakeholder management across technical and non-technical teams
  • Comfortable working in ambiguous, unstructured environments

Technical / Domain Exposure

  • Experience with:
  • ERP systems and operational data
  • Industrial / OT (Operational Technology) environments
  • Data pipelines and infrastructure
  • Exposure to cloud platforms (Azure preferred)

What Success Looks Like

  • Early: Assess current state and define roadmap
  • Mid-term: Deliver initial AI-driven wins with measurable impact
  • Long-term: Build scalable AI capability across the business

Why This Role Stands Out

  • First AI hire → real ownership and influence
  • Greenfield environment → build it your way
  • High visibility → direct exposure to senior leadership
  • Global scope → impact across multiple business units
  • Practical focus → real results, not just experimentation

Ideal Candidate Profile

  • Pragmatic and execution-focused (not overly academic)
  • Comfortable working with imperfect data and evolving systems
  • Strong communicator who can influence across functions
  • Excited by the opportunity to build something from scratch


Apply