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Kyndryl Graduate Program - Data Scientist - Job Opportunity at Kyndryl

Liverpool, GB
Full-time
Entry-level
Posted: June 21, 2025
On-site
£28,000-£35,000 per year for graduate programs in Liverpool, with rapid progression to £45,000-£55,000 within 2-3 years based on the structured development pathway and premium client exposure typical of major consulting firms

Benefits

Comprehensive 2-year graduate program with structured learning and development pathway providing accelerated career advancement compared to traditional entry-level positions
Hands-on experience with flagship clients offering exposure to high-profile projects and premium market segments
Rotation opportunities across different business units enabling broad skill development and internal networking
Shadowing programs with senior professionals providing mentorship and insider knowledge of corporate dynamics
Specialization pathways allowing focused expertise development in high-demand technical areas
Certification opportunities across four major technology platforms enhancing market value and career mobility
Global team collaboration experience building international business acumen and cross-cultural competencies
Volunteer community activities supporting personal brand development and corporate social responsibility engagement
Dynamic start-up atmosphere within an established enterprise combining innovation with stability
Access to cutting-edge AI Innovation Lab resources providing exposure to emerging technologies and research opportunities

Key Responsibilities

Drive transformative business impact by serving as the critical bridge between complex business challenges and innovative data-driven solutions, directly influencing strategic decision-making across mission-critical technology systems
Lead comprehensive business analysis and requirements gathering processes, translating high-level organizational objectives into actionable data science problems that deliver measurable value to enterprise clients
Execute end-to-end data science workflows including advanced data collection, exploratory analysis, and pattern recognition to uncover strategic insights that guide business hypothesis formation and validation
Architect and develop sophisticated statistical and mathematical models that challenge conventional approaches, creating breakthrough solutions for intricate business challenges across banking, healthcare, automotive, and government sectors
Deploy production-ready machine learning models as scalable code solutions, ensuring sustained business value delivery throughout model lifecycles while maintaining optimal performance standards
Navigate complex enterprise business processes to identify critical operational inefficiencies and craft data-driven solutions that drive meaningful organizational transformation
Establish and enforce data governance standards and policies that protect organizational assets while ensuring data security, privacy, accuracy, availability, and usability across all business functions
Contribute to flagship client projects that directly impact global technology infrastructure supporting banks, stock markets, airlines, and healthcare systems
Participate in strategic consulting engagements that shape how major corporations leverage data science for competitive advantage
Lead knowledge transfer and capability building initiatives within the AI Innovation Lab, contributing to organizational learning and best practice development

Requirements

Education

Bachelor's or Master's degree in a quantitative discipline, such as Data Science, Mathematics, Statistics, Computer Science or a related field

Experience

Graduate level (0-2 years experience)

Required Skills

Passionate about extracting insights from data to solve real-world problems Experience in programming languages Comfortable working with data visualisation tools (e.g. Seaborn, Tableau) Knowledgeable in statistical analysis, machine learning concepts, and data wrangling techniques Curious, analytical, and detail-oriented with a strong problem-solving mindset A strong communicator who can explain technical findings to both technical and non-technical audiences Eager to learn, grow, and contribute within a collaborative team environment Previous experience in consulting is a plus Understanding of IT operations and IT service management frameworks Basic understanding of core services offered by established cloud Hyperscalers (e.g. Microsoft, AWS, Google Cloud etc.)
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Sauge AI Market Intelligence

Industry Trends

The enterprise data science market is experiencing unprecedented growth as organizations accelerate digital transformation initiatives, with companies investing heavily in AI and machine learning capabilities to maintain competitive advantage in an increasingly data-driven economy. This trend is particularly pronounced in mission-critical sectors like financial services, healthcare, and government where Kyndryl operates. There is a significant shift toward hybrid cloud and multi-cloud strategies in enterprise IT infrastructure, creating massive demand for data scientists who can work across diverse technology platforms and understand both on-premises and cloud-based data ecosystems. This creates substantial opportunities for professionals who can bridge traditional IT operations with modern data science practices. The market is seeing increased emphasis on responsible AI and data governance, with regulatory requirements driving demand for data scientists who understand compliance, privacy, and ethical AI implementation. Organizations are prioritizing candidates who can balance innovation with risk management and regulatory compliance. Enterprise consulting in data science is becoming more specialized, with companies seeking professionals who can translate complex technical concepts into business value and work directly with C-level executives on strategic initiatives. This consulting-focused approach is becoming a key differentiator in the market.

Role Significance

Likely working within small, agile data science teams of 3-5 professionals per project, with exposure to larger cross-functional teams of 10-15 members including business analysts, IT architects, and client stakeholders
This is a premium graduate entry position with accelerated responsibility progression, designed to fast-track high-potential candidates into senior data science roles within 2-3 years. The role carries significant weight due to direct client exposure and strategic project involvement from day one.

Key Projects

Implementation of predictive analytics solutions for financial services risk management and fraud detection systems Development of machine learning models for healthcare outcomes optimization and patient care pathway analysis Creation of real-time monitoring and anomaly detection systems for critical infrastructure and government operations Design and deployment of customer behavior analytics and recommendation engines for retail and e-commerce clients Building automated decision-making systems for supply chain optimization and logistics management

Success Factors

Developing strong business acumen alongside technical skills is crucial, as the role requires translating complex data insights into actionable business recommendations that drive strategic decision-making at the executive level. Building exceptional communication and presentation skills will be critical for success, as the role involves regularly presenting findings to senior client stakeholders and non-technical audiences who make million-dollar decisions based on your analysis. Cultivating adaptability and continuous learning mindset is essential given the rapid evolution of AI/ML technologies and the diverse industry sectors served, requiring quick mastery of new tools, techniques, and domain knowledge. Establishing strong consulting and client relationship management capabilities will differentiate top performers, as success depends on building trust with enterprise clients and understanding their unique business challenges and constraints. Developing expertise in enterprise-scale data infrastructure and cloud platforms is vital, as most projects involve large, complex data ecosystems that require understanding of scalability, performance, and integration challenges.

Market Demand

Very high demand driven by the critical shortage of data science talent in enterprise consulting and the increasing reliance on data-driven decision making across all business sectors, particularly in mission-critical infrastructure

Important Skills

Critical Skills

Programming proficiency in Python or R is absolutely essential as these are the primary languages for data manipulation, statistical analysis, and machine learning model development in enterprise environments. Without strong programming skills, it's impossible to effectively process large-scale enterprise datasets or deploy production-ready solutions. Statistical analysis and machine learning knowledge forms the core foundation of the role, as all business recommendations must be based on rigorous analytical methods and validated models. Understanding concepts like hypothesis testing, regression analysis, classification, and clustering is fundamental to providing credible insights to enterprise clients. Business communication and presentation skills are critical because success depends entirely on the ability to translate complex technical findings into clear, actionable recommendations for non-technical stakeholders who make strategic business decisions based on your analysis. Data visualization capabilities using tools like Tableau and Seaborn are essential for making complex patterns and insights accessible to business audiences, as visual storytelling often determines whether recommendations are understood and implemented by client organizations.

Beneficial Skills

Cloud platform knowledge (AWS, Azure, Google Cloud) is increasingly valuable as most enterprise clients are migrating to hybrid cloud architectures, and understanding cloud-native data services and deployment models significantly enhances your ability to design scalable solutions. Consulting experience or business acumen provides significant advantage in client-facing roles, as understanding business strategy, market dynamics, and organizational change management helps in crafting recommendations that are not only technically sound but also practically implementable. IT operations and service management framework knowledge is highly beneficial given Kyndryl's focus on mission-critical infrastructure, as understanding ITIL, DevOps, and enterprise architecture principles helps in designing data solutions that integrate seamlessly with existing technology ecosystems.

Unique Aspects

This role offers rare direct access to mission-critical infrastructure systems that power global financial markets, healthcare systems, and government operations, providing unparalleled exposure to enterprise-scale data challenges and their real-world impact on society.
The combination of structured graduate program with immediate flagship client exposure creates an accelerated learning environment that typically takes 5-7 years to achieve in traditional career paths.
Working within the Liverpool AI Innovation Lab provides access to cutting-edge research and development opportunities while being part of a global technology services organization with extensive resources and market reach.
The role uniquely bridges traditional IT infrastructure management with modern data science applications, creating expertise in both legacy system integration and emerging AI technologies that is highly valued in the enterprise market.

Career Growth

Rapid progression typical within 18-24 months to mid-level responsibilities, with senior roles achievable within 3-4 years due to the intensive training program and high-profile client exposure

Potential Next Roles

Senior Data Scientist roles within 2-3 years with increased project leadership responsibilities and specialized domain expertise Data Science Manager or Team Lead positions overseeing junior data scientists and managing client relationships Principal Data Scientist or Technical Lead roles focusing on solution architecture and advanced research initiatives Management Consultant specializing in data strategy and digital transformation for enterprise clients Product Manager roles for data science platforms or AI-powered enterprise solutions

Company Overview

Kyndryl

Kyndryl is a global technology services company spun off from IBM in 2021, specializing in managing and modernizing mission-critical technology infrastructure for large enterprises and government organizations. The company operates in over 60 countries and manages some of the world's most complex IT environments.

Kyndryl is positioned as a major player in the enterprise IT services market, competing with companies like Accenture, Deloitte, and Capgemini, with particular strength in mainframe and legacy system modernization combined with cutting-edge AI and cloud capabilities.
The Liverpool location represents a strategic UK presence with the AI Innovation Lab serving as a key technology hub for European operations, offering exposure to both domestic and international clients across multiple time zones and regulatory environments.
The company culture emphasizes diversity, inclusion, and continuous learning, with a startup-like atmosphere that encourages innovation while leveraging the stability and resources of a large enterprise, creating an environment conducive to rapid professional growth and skill development.
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