Data science hiring in 2026 looks nothing like it did three years ago. Earlier, data science roles mostly required you to analyse spreadsheets at length. But come 2026, and now companies are looking for builders of machine learning systems, GenAI pipelines, and production-grade models that have a real impact on business metrics. Easy to guess, this shift has created a sharp divide between ordinary data roles and the top data science jobs that take the pole position of decision-making. These roles mix statistics, engineering, cloud platforms, and large language models into one high-impact skillset. From global tech firms to airlines and consumer giants, companies now compete for scientists who can turn raw data into automated intelligence. In this list, we list ten such roles in the market right now, and analyse how they shape this new era of data scientists – complete with their demands and promises.
So if you are a data scientist, make sure to go through this list and apply for the role that resonates the most with you and your experience.
Early-Career (0–3 Years)
These roles are built for fresh graduates and junior data scientists who want to work on real business data and production systems.
1. American Express – Analyst – Data Analytics
Company Snapshot
American Express is a global financial services leader with over 175 years of innovation. The company is known for its strong values, customer-first culture, and commitment to employee growth and well-being.
Salary
Competitive base salary with bonus incentives, medical, dental, vision, life insurance, and retirement benefits.
What You Will Do
You will support digital and product teams by running experiments and using data to guide business decisions.
Your key responsibilities include:
- Delivering analytics and experimentation insights for digital and product teams
- Designing experiments, defining hypotheses, and building test plans
- Turning test results into clear recommendations for business teams
- Working with enterprise data systems to ensure accurate analysis
- Supporting new analytics and experimentation tools
- Helping prevent account overdues and supporting client account recovery
Eligibility Criteria
- Advanced degree in Finance, Engineering, Mathematics, Computer Science, or a similar field
- Strong programming skills
- Experience with Python, R, SQL, Hive, Spark, or large-scale data systems
- Experience handling large datasets and working with data science methods
- Strong communication and collaboration skills
- Attention to detail in a fast-moving, cross-functional environment
Preferred Skills
Why You Should Apply
This role places you at the center of how American Express improves digital products through real data. With one of the world’s most trusted financial brands, you will shape customer experiences across markets and run experiments that influence how millions of users interact with Amex platforms.
2. United Airlines – Associate Data Scientist
Company Snapshot
United Airlines is one of the world’s largest airlines. Its Digital Technology and Analytics teams use data, AI, and technology to improve airline operations and customer experience.
Salary
Not disclosed in the listing.
What You Will Do
You will build data-driven solutions that improve airline operations, revenue, and customer experience.
Your responsibilities include:
- Working with data scientists and business teams to build ML models
- Analyzing operations data to make data-driven recommendations
- Using machine learning and optimization tools to solve business problems
- Monitoring deployed models and supporting scalable deployments
- Researching new machine learning methods and sharing knowledge
- Presenting insights clearly to leaders and teams
- Working with data engineering and operations teams on live projects
Eligibility Criteria
- Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, Economics, or related fields
- 0–3 years of experience
- Strong analytical and problem-solving skills
- Programming in Python or R, SQL, and Excel
- Knowledge of machine learning methods such as Decision Trees, Random Forest, XGBoost, GBM, and K-Means
- Understanding of probability and statistics
- Ability to explain technical ideas to business teams
- Strong teamwork and communication skills
Preferred Skills
- Experience with deep learning, NLP, or computer vision
- Experience with cloud platforms such as AWS or Azure
Why You Should Apply
This role gives you hands-on experience working with real airline data that affects flights, revenue, and passengers every day. You will help automate operations, improve customer engagement, and drive business decisions using machine learning. It is a strong entry-level role for building a career in applied data science at global scale.
3. Nestlé – Junior Data Scientist (Demand Forecasting)
Company Snapshot
Nestlé is the world’s largest food and beverage company, operating in over 180 countries. It uses data, technology, and advanced analytics to improve demand planning, supply chains, and product availability across global markets.
Salary
Not mentioned in the listing.
What You Will Do
You will build and improve forecasting models that predict product demand.
Your work will include:
- Developing and maintaining demand forecasting models
- Improving forecasting tool accuracy and reliability
- Running back-testing to validate model performance
- Working closely with demand planners and analysts
- Using business inputs to improve forecast quality
Eligibility Criteria
- Bachelor’s degree in Mathematics, Engineering, Computer Science, or Data Science
- 2+ years of experience in demand planning or forecasting models
- 2+ years of experience with Python or PySpark
- 2+ years of experience using Azure, Snowflake, and Databricks
Why You Should Apply
This role puts you directly into real business forecasting used by one of the world’s largest consumer companies. Your models will help Nestlé decide how much to produce, where to ship, and how to meet customer demand more accurately. It offers hands-on exposure to enterprise-scale data, cloud platforms, and real production systems used in global operations.
4. Birdeye – Data Scientist
Company Snapshot
Birdeye is an AI-powered customer experience and reputation management platform used by over 150,000 businesses worldwide. It helps companies manage reviews, social media, and customer engagement to grow sales and improve brand trust.
Salary
Not mentioned in the listing.
What You Will Do
You will build and deploy AI and data science solutions that power Birdeye’s customer experience platform.
Your work will include:
- Developing custom data models and algorithms
- Building and improving machine learning and GenAI models
- Applying LLMs and NLP to solve business problems
- Communicating insights and recommendations to product managers and executives
- Deploying AI services using cloud platforms and APIs
- Working with data stored in SQL and NoSQL systems
Eligibility Criteria
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- 2–3 years of experience in data science or AI roles
- Strong Python programming skills
- Experience with prompt engineering, LLMs, and GenAI
- Hands-on experience with NLP tools such as BERT, NLTK, SpaCy, or GloVe
- Experience using AWS, Azure, or GCP
- Experience with Docker and API deployment frameworks like FastAPI or gRPC
Why You Should Apply
Birdeye builds AI products used by thousands of businesses every day. In this role, your models and LLM systems will directly improve how companies manage customers, reputation, and digital engagement. If you want to work on real GenAI and NLP systems that run at scale in a product company, this role gives you that opportunity.
Mid-Level (3–5 Years)
These roles expect you to own models, work with real business data, and deliver production-ready analytics.
5. AB InBev GCC India – Data Scientist
Company Snapshot
AB InBev is one of the world’s largest beverage companies, known for brands such as Budweiser and Corona. Its Global Capability Center in India uses data and analytics to support operations, finance, people, and technology teams across the business.
Salary
Not disclosed in the listing.
What You Will Do
You will design and deliver data science solutions that help teams make better business decisions.
Your work will include:
- Building and maintaining data science models using Python, pandas, and NumPy
- Performing feature engineering and statistical validation of models
- Writing clean, modular, and well-documented code
- Working with business and technical teams to translate problems into data solutions
- Reading and improving existing codebases
- Using Git for version control and collaboration
- Writing and optimizing SQL queries
- Preparing models for production and decision support
- Documenting assumptions, processes, and outputs
- Keeping up with new data science tools and methods
Eligibility Criteria
- Bachelor’s or Master’s degree in Computer Science, AI, ML, or related fields
- Minimum 3 years of hands-on experience in data science or analytics
- Strong Python skills with pandas and NumPy
- Ability to validate models and features using statistics
- Intermediate SQL skills
- Experience using Git
- Comfortable working with existing code
Preferred Skills
- Object-oriented programming in Python
- Knowledge of test-driven development
- Understanding of model deployment and tracking
Why You Should Apply
This role gives you the chance to work on real business problems in a global company using modern data science practices. You will build models that directly support decisions in operations, finance, and technology, and your work will be used in production systems. It is a strong opportunity to grow as a hands-on data scientist in a large, data-driven organization.
6. Gartner – Data Scientist (Global Sales & Services Operations)
Company Snapshot
Gartner is a global research and advisory company that helps business and technology leaders make better decisions. It supports around 14,000 enterprises across 90 countries using data, analysis, and expert insights.
Salary
Competitive salary with medical insurance, paid time off, parental leave, and employee assistance benefits.
What You Will Do
You will build AI systems that help Gartner’s global sales teams work smarter. Your work will focus on turning large volumes of text and client data into useful insights.
Your core responsibilities include:
- Building LLM-based agents to process and act on business information
- Using Generative AI and NLP to analyze emails and call transcripts
- Predicting client interest from digital activity and recommending next actions
- Running statistical and machine learning models on client retention data
- Creating tools to process structured and unstructured datasets
- Engineering features to train machine learning models
Eligibility Criteria
- Bachelor’s, Master’s, or PhD in Computer Science, Math, Statistics, Economics, or similar
- 3+ years of data science experience in real production systems
- 3+ years of Python and statistical analysis
- At least 2 years working with:
- NLP and information retrieval
- Prompt engineering and LLMs
- Recommendation systems
- Statistical modeling
- Experience working with large datasets and user behavior data
Why You Should Apply
This role places you inside Gartner’s $4.9 billion sales engine, where your models will directly influence how global clients are served. You will build AI systems that guide real business decisions for thousands of sales professionals worldwide. Just think of the kind of exposure this can bring to your portfolio.
Senior (5+ Years)
These are high-impact roles where data science directly shapes products, revenue, and business strategy.
7. Expedia Group – Data Scientist III – Analytics
Company Snapshot
Expedia Group builds technology that powers travel booking, protection, and services for customers around the world.
Salary
Not mentioned in the job listing.
What You Will Do
You will work with product teams to use data from many sources to find new product ideas and spot problems in current customer journeys.
- You will run A/B tests to measure how new features perform and turn results into clear financial impact.
- You will build and track key metrics using dashboards so teams can see how products are doing in real time.
- You will share insights with product leaders and business teams so they can make better decisions.
- You will support product launches and roadmap planning using data and analysis.
Eligibility Criteria
- Bachelor’s degree in Statistics, Mathematics, Economics, Data Science, or a related field
- 5 or more years of experience in analytics, mainly in product analytics and measurement
- Strong skills in A/B testing, causal analysis, and deep analysis of experiment results
- Strong experience with SQL, Python, Databricks, AWS, or similar big-data tools
- Experience working with Product and Finance teams
- Strong problem-solving and leadership skills
Preferred
- Knowledge of price modeling and time-series analysis
- Experience with regression and classification models
- Exposure to recommendation systems, multi-armed bandits, or reinforcement learning
Why You Should Apply
This role puts you at the center of product and business decisions inside Expedia’s operations. Your analysis will directly shape how travel products are built, tested, and launched for travelers. The best part about this role – every product change you bring about is backed by experiments, dashboards, and real customer insights.
8. Mastercard – Senior Data Scientist
Company Snapshot
Mastercard is a global payments technology company operating in over 200 countries and territories. It builds secure digital payment systems that power businesses, governments, and financial institutions worldwide.
Salary
Not mentioned in the listing.
What You Will Do
You will build and run data science systems that improve how digital payments perform across Mastercard’s products.
Your work will include:
- Building machine learning models for product and sales optimization
- Creating AI systems that automate predictive analytics
- Processing and analyzing high-volume payment data
- Testing new algorithms and tools
- Supporting product teams with data-driven insights
- Turning data into measurable business impact
Eligibility Criteria
- Degree in Computer Science, Data Science, Mathematics, Statistics, or related field
- Experience in data mining, analytics, and quantitative modeling
- Strong skills in Python, SQL, Spark, and Hadoop tools
- Knowledge of machine learning frameworks and data systems
- Experience working with large datasets
- Ability to work with business and technical teams
Why You Should Apply
This role places you at the core of how global digital payments improve and scale. Your models will directly shape how billions of transactions perform across markets, products, and customers. You will work with global teams, high-volume data, and real financial systems, giving you rare exposure to applied data science at one of the world’s most influential technology companies.
Principal / Lead (8+ Years)
These roles sit at the architecture and platform level, where you design and run enterprise-scale AI systems.
9. TCS – Data Scientist
Company Snapshot
Tata Consultancy Services (TCS) is a global IT services and consulting company. It helps enterprises use technology, data, and AI to improve business performance and operations.
Salary
Not mentioned in the listing.
What You Will Do
You will design and deliver AI systems that improve productivity and efficiency across the business.
Your work will include:
- Designing and building AI systems with a focus on NLP and LLM applications
- Developing and improving machine learning algorithms
- Using data from many sources to identify and validate business opportunities
- Working with internal and external teams to define AI system requirements
- Deploying AI and ML solutions into real business workflows
- Monitoring model performance and improving accuracy over time
- Keeping up with new AI and machine learning methods and applying them to system design
Eligibility Criteria
- 8 to 15 years of experience
- Strong knowledge of data science tools and software development practices
- Proficiency in Python and Git
- Experience with NLP, NLU, and large language models
- Strong background in statistics, machine learning, causal inference, and experimental design
Why You Should Apply
This role puts you at the center of TCS’s AI transformation. You will work on large-scale NLP and LLM systems that directly improve how the business operates. If you want to build real AI systems that go into production and drive measurable outcomes, this role gives you that platform.
10. NatWest Digital X – Data Scientist
Company Snapshot
NatWest Digital X is the digital and technology arm of NatWest Group. It builds secure and simple digital banking experiences for millions of customers.
Salary
Not mentioned in the listing.
What You Will Do
You will work at the intersection of data science and engineering to improve digital banking.
Your work will include:
- Working with business teams to understand problems and data needs
- Building predictive and AI models using machine learning, NLP, and deep learning
- Creating, training, and monitoring ML and LLM models
- Automating data pipelines and model deployment
- Using data visualisation and storytelling to explain results
- Providing insights that help teams make better decisions
Eligibility Criteria
- 8 to 12 years of experience in Python and machine learning
- Experience with cloud platforms such as AWS, Google AI, or IBM Watson
- Strong knowledge of LLMs, transformer models, and NLP
- Experience with LangChain, LangGraph, and MCP for agent-based systems
- Strong foundation in machine learning, predictive modelling, and deep learning
- Experience with Tableau or another data visualisation tool
Why You Should Apply
NatWest Digital X builds the technology that powers modern banking. In this role, your models and AI systems will directly shape how customers interact with digital financial services. You will work on large-scale data, real users, and real business impact while building advanced AI systems in a secure, regulated environment.
Conclusion
The data science market in 2026 is all about impact. Every role on this list gives you direct access to real business systems, real revenue, and real decisions. From airline operations and cloud platforms to finance, retail, and global payments.
If you see a role that matches your skills and ambition, do not wait. In all my experience with job applications, people who move early reap the benefits, not those who overthink. Update your profile, shortlist two or three roles, and start applying today.
And before you do, make sure your resume actually reflects the kind of data scientist these companies are hiring. Read our companion guide on how to write a modern data science resume for 2026, where we break down how to showcase projects, models, and business impact the right way.
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