Specialist za podatkovno znanost in UI / Specialist Data Science & AI

📍 Job Overview

Job Title: Specialist za podatkovno znanost in UI / Specialist Data Science & AI

Company: Novartis

Location: Ljubljana, Slovenia

Job Type: Full time, Temporary (2-year fixed-term contract)

Category: Data Science & Artificial Intelligence (with a strong focus on operational efficiency)

Date Posted: 2026-08-18

Experience Level: Entry-level to Junior (0-2 years)

Remote Status: Hybrid

🚀 Role Summary

• Drive the adoption of Agentic and AI capabilities within TechOps processes to achieve significant productivity and efficiency gains.

• Foster AI fluency across IT/OT and business teams, establishing a network of AI champions to facilitate practical, hands-on solution development.

• Lead the identification and prioritization of use cases from the ground up, ensuring alignment with site leadership and overseeing the successful implementation of AI solutions.

• Act as a liaison for local requirements, feeding insights back into global product roadmaps for continuous improvement of AI platforms.

• Implement robust governance frameworks, meticulously track benefits, and report on key metrics, including productivity and FTE impact.

📝 Enhancement Note: While the title includes "Data Science & AI," the core responsibilities and requirements point towards a "Revenue Operations" or "GTM Operations" adjacent role, specifically focused on applying AI and automation within operational technology (TechOps) to drive efficiency. The emphasis is on practical, low-code/no-code implementation and user enablement rather than deep theoretical data science. This role is crucial for operational excellence and streamlining business processes through AI.

📈 Primary Responsibilities

• Champion the end-to-end adoption of Agentic and AI capabilities across both local and global TechOps processes, embedding AI-enabled work practices into daily operations.

• Develop AI literacy within IT/OT and business teams, establish and lead Agentic/AI champion networks, and empower hands-on development of no-code/low-code agentic solutions.

• Lead bottom-up identification of high-value use cases, prioritize opportunities in collaboration with site leadership, and oversee the delivery, scaling, and sustained adoption of Agentic & AI solutions.

• Promote the utilization of globally available Agentic & AI platforms, continuously channeling site-specific requirements, identified gaps, and enhancement opportunities into global product backlogs.

• Establish clear governance structures, diligently track benefits realization, and generate comprehensive reports, including detailed analysis of productivity and FTE impact, while maintaining a forward-looking multi-year Agentic & AI roadmap.

• Collaborate closely with Global DDIT Ops and DSAI teams to ensure readiness of data, platforms, integrations, and security, thereby enabling data self-service capabilities for local sites.

• Lead change management initiatives and foster cultural transformation, ensuring employees embrace AI as a tool for augmenting their work and actively leverage Agentic & AI solutions in their day-to-day responsibilities.

📝 Enhancement Note: The responsibilities highlight a strong emphasis on change management, user enablement, and driving adoption, which are critical functions within a GTM or Revenue Operations context. The role requires influencing stakeholders and managing the human element of technology implementation, ensuring that AI solutions translate into tangible business value.

🎓 Skills & Qualifications

Education: Specific educational requirements are not explicitly stated, but a background in a related technical or business field is implied.

Experience:

• Minimum of 1 year of experience in Data Science and AI.

• Demonstrated experience with enterprise AI assistants, preferably Microsoft Copilot (M365 Copilot, Copilot Studio).

• Proven ability to build agentic solutions using no-code/low-code platforms (e.g., Power Platform, Copilot Studio). Required Skills:

• Strong interest and curiosity in AI development and its applications.

• Hands-on experience with enterprise AI assistants, particularly Microsoft Copilot and Copilot Studio.

• Proven ability to develop agentic solutions using no-code/low-code platforms, including prompt design, workflow creation, and basic integrations.

• Practical understanding of agent orchestration, reusable patterns, and scaling AI agents in operational environments.

• Basic data science and analytics skills, including KPI definition, descriptive analysis, SQL knowledge, and interpretation of AI outputs.

• Excellent communication skills, a proactive "can-do" attitude, and a strong, curious approach.

• Ability to dive deep into business needs and translate them into effective AI solutions.

• Strong interest in automation and robotics. Preferred Skills:

• Knowledge of pharmaceutical processes and the pharmaceutical industry.

• Experience with data fundamentals: ability to consume, combine, and interpret data from enterprise systems (e.g., MES, ERP, LIMS).

• Basic understanding of data quality, data access, and data governance principles.

• Python programming experience.

• Practical experience with broader automation and robotics initiatives.

📝 Enhancement Note: The "1+ years of experience" suggests that candidates with a strong internship or project-based background in AI/Data Science, particularly with hands-on low-code/no-code experience, will be competitive. The emphasis on Microsoft Copilot and Power Platform indicates a need for familiarity with the Microsoft ecosystem.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase practical examples of AI solutions developed using no-code/low-code platforms (e.g., Power Platform, Copilot Studio).

• Demonstrate experience in designing prompts, workflows, and basic integrations for AI agents.

• Present case studies of how AI was used to solve specific business problems or improve operational efficiency.

• Include examples of data analysis or interpretation of AI outputs, even if basic.

• Highlight any contributions to automation or robotics projects. Process Documentation:

• Evidence of defining KPIs and measuring the impact of AI initiatives.

• Documentation of workflow designs and implemented automation processes.

• Examples of data interpretation and reporting on AI solution performance.

• Any experience with data governance or data quality improvements related to AI projects.

📝 Enhancement Note: Candidates should prepare to showcase their practical application of AI tools, particularly in a business context. A portfolio demonstrating the ability to translate business needs into functional AI solutions, even if built with low-code/no-code tools, will be highly advantageous. Highlighting the impact and measurable results of these solutions is crucial.

💵 Compensation & Benefits

Salary Range: €26,600.00 - €49,400.00 annually (gross base salary)

Benefits:

• Insurance plans

• Retirement plans

• Wellbeing resources

• Global recognition programs

• Flexible working options

• Hybrid working options

• Minimum 14 weeks paid parental leave

Working Hours: The job description implies a standard full-time work week, likely around 40 hours, with flexibility offered through hybrid working arrangements.

📝 Enhancement Note: The provided salary range is for Ljubljana, Slovenia. Based on local market data for junior-level Data Science & AI specialists with 1-2 years of experience, this range appears competitive. The inclusion of "Band Level 3" suggests a structured pay scale within Novartis. The benefits package is comprehensive, reflecting typical offerings for a large multinational pharmaceutical company.

🎯 Team & Company Context

🏢 Company Culture

Industry: Pharmaceutical and Biotechnology. Novartis is a global leader in healthcare, focused on discovering, developing, manufacturing, and marketing a wide range of prescription medicines.

Company Size: Novartis is a large multinational corporation, employing tens of thousands of people globally. This scale suggests a structured environment with established processes and opportunities for cross-functional collaboration.

Founded: Novartis was formed in 1996 through the merger of Ciba-Geigy and Sandoz. This long history indicates stability and a deep-rooted presence in the industry.

Team Structure:

• The role sits within the TechOps (Technical Operations) domain, likely within the IT or Digital Transformation functions.

• It involves close collaboration with global DDIT Ops (Digital Information and Technology Operations) and DSAI (Data Science & AI) teams.

• The role also requires establishing and leading a network of "Agentic/AI champions" within local and global business teams, indicating a distributed model of AI adoption. Methodology:

• Focus on driving adoption of Agentic and AI capabilities through practical, hands-on solutions (no-code/low-code).

• Emphasis on building AI fluency and enabling business users.

• Structured approach to use case identification, prioritization, and governance.

• Continuous feedback loop between local site needs and global product development.

• Commitment to change management and cultural adoption of AI.

Company Website: https://www.novartis.com/

📝 Enhancement Note: Novartis's culture likely emphasizes innovation, scientific rigor, and patient focus. For this role, expect a blend of corporate structure and a fast-paced digital transformation agenda, particularly in adopting AI. The "LI-Hybrid" tag suggests a commitment to flexible work arrangements, balancing in-office collaboration with remote flexibility.

📈 Career & Growth Analysis

Operations Career Level: This is an entry-level to junior specialist role (Band Level 3), suitable for individuals with 1-2 years of experience or strong academic/project backgrounds in AI/Data Science and automation. It's a foundational role for developing expertise in AI-driven operational efficiency.

Reporting Structure: The role reports within the TechOps function and collaborates with global IT and AI teams. The specific reporting line would be to a manager within the local TechOps or Digital Transformation department.

Operations Impact: This role directly impacts operational efficiency and productivity within TechOps by embedding AI solutions. It contributes to cost savings, improved process execution, and faster delivery of value through automation and intelligent augmentation, aligning with broader GTM and operational excellence objectives.

Growth Opportunities:

• Deepen expertise in AI, Agentic capabilities, and specific platforms like Microsoft Copilot and Power Platform.

• Develop strong change management and user enablement skills, crucial for GTM and Ops leadership.

• Gain exposure to pharmaceutical industry processes, providing a specialized domain knowledge.

• Potential to transition into more senior AI/Data Science roles, specialized automation roles, or broader operational management positions within Novartis.

• Opportunities to contribute to global product roadmaps and influence future AI strategy.

📝 Enhancement Note: The fixed-term contract (2 years) suggests this role may be part of a specific project or initiative to accelerate AI adoption. While offering excellent experience, candidates should be aware of the contract duration and inquire about potential extensions or conversion to permanent roles during the application process.

🌐 Work Environment

Office Type: The role is designated as "LI-Hybrid," indicating a blend of on-site and remote work. This suggests a modern office environment that supports collaborative work and individual focused tasks.

Office Location(s): Ljubljana, Slovenia. Novartis has a significant presence in Ljubljana, likely offering a well-equipped office space.

Workspace Context:

• Access to standard office technology and potentially specialized AI/automation tools and platforms.

• Opportunities for collaboration with local and global IT/TechOps teams.

• A dynamic environment focused on digital transformation and AI adoption.

• The hybrid model allows for flexibility in managing personal work styles and project needs.

Work Schedule: A standard full-time schedule is expected, with hybrid flexibility allowing for a balance between office presence for collaboration and remote work for focused tasks. The specific arrangement will likely be defined by team needs and manager discretion.

📝 Enhancement Note: The hybrid work model is a significant aspect of the work environment, offering flexibility. Candidates should clarify the expected balance between in-office and remote days with the hiring manager during the interview process.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of CVs (in Slovenian and English) and potentially a brief call to assess basic qualifications and interest.

• Technical/Skills Assessment: Likely an interview focusing on practical AI/low-code skills, understanding of concepts like prompt engineering, agent orchestration, and experience with tools like Microsoft Copilot.

• Case Study/Problem-Solving: Candidates may be asked to discuss how they would approach a specific business problem using AI, or present a past project from their portfolio.

• Cultural Fit & Collaboration: Interviews to assess communication skills, proactivity, curiosity, and ability to work within a hybrid, global team environment.

• Manager Interview: Final discussion with the hiring manager to confirm fit for the role and team.

Portfolio Review Tips:

• Quantify Impact: For any past projects, focus on measurable outcomes (e.g., time saved, efficiency gained, issues resolved).

• Showcase Practicality: Highlight your ability to build functional solutions, especially using no-code/low-code tools.

• Demonstrate Understanding: Clearly articulate the business problem you solved and why AI was the appropriate solution.

• Tool Proficiency: Be ready to discuss your experience with Microsoft Copilot, Power Platform, or similar tools.

• Process Thinking: Explain the steps you took from understanding a need to deploying a solution.

Challenge Preparation:

• Be prepared to discuss hypothetical scenarios: "How would you use AI to improve X process in a pharmaceutical manufacturing setting?"

• Understand the capabilities and limitations of enterprise AI assistants like Microsoft Copilot.

• Think about how to drive adoption and manage change when introducing new AI tools.

• Familiarize yourself with Novartis's mission and values, and how AI can contribute to them.

📝 Enhancement Note: Given the emphasis on no-code/low-code and practical application, candidates should prepare to walk through their portfolio projects with a focus on the "how" and the "why," rather than just the "what." Demonstrating a proactive and problem-solving mindset will be key.

🛠 Tools & Technology Stack

Primary Tools:

• Enterprise AI Assistant: Microsoft Copilot (M365 Copilot, Copilot Studio) - Core requirement.

• No-code/Low-code Platforms: Power Platform (Power Apps, Power Automate) - Essential for building solutions.

• AI Agent Development: Tools for prompt design, workflow creation, and basic integrations.

Analytics & Reporting:

• Data Analysis: Basic data science and analytics skills, including SQL knowledge for data interpretation.

• KPI Definition: Ability to define and track key performance indicators for AI initiatives.

• Reporting: Experience in reporting on benefits, productivity, and FTE impact.

CRM & Automation:

• Automation & Robotics: Strong interest and practical experience in automation and robotics.

• System Integration: Experience with basic integrations for AI solutions.

• Enterprise Systems (Desirable): Familiarity with MES, ERP, LIMS systems for data consumption.

📝 Enhancement Note: The technology stack is heavily skewed towards the Microsoft ecosystem, with a strong emphasis on enterprise AI assistants and low-code development tools. Familiarity with these specific platforms will be a significant advantage.

👥 Team Culture & Values

Operations Values:

• Innovation & Curiosity: A drive to explore and adopt new AI technologies.

• Efficiency & Productivity: A focus on measurable gains and operational excellence.

• Collaboration: Working effectively with local and global teams, and fostering AI champions.

• User-Centricity: Translating business needs into practical, user-friendly AI solutions.

• Data-Driven Approach: Utilizing data to identify opportunities, measure impact, and inform decisions.

Collaboration Style:

• Hybrid and global collaboration, requiring strong virtual communication skills.

• Cross-functional engagement with IT, OT, and business units.

• A culture of knowledge sharing and empowerment through AI champions.

• Proactive engagement and a willingness to "dive deep" to understand and solve problems.

📝 Enhancement Note: Novartis emphasizes diversity and inclusion. Candidates should demonstrate an inclusive mindset and an ability to collaborate effectively with colleagues from diverse backgrounds and geographies. The "can-do" attitude and proactive approach are key cultural indicators.

⚡ Challenges & Growth Opportunities

Challenges:

• Driving Adoption: Overcoming resistance to change and ensuring widespread adoption of AI tools across diverse user groups.

• Bridging Technical Gaps: Enabling users with varying levels of technical proficiency to leverage AI effectively.

• Integrating with Legacy Systems: Ensuring smooth data flow and integration with existing enterprise systems (MES, ERP, LIMS).

• Measuring ROI: Quantifying the tangible benefits and productivity gains from AI initiatives.

• Staying Current: Keeping pace with the rapid advancements in AI technology and its applications.

Learning & Development Opportunities:

• Specialized training on Microsoft Copilot, Power Platform, and other AI tools.

• Development in data science, analytics, and automation techniques.

• Opportunities to gain in-depth knowledge of pharmaceutical operations and processes.

• Skill development in change management, stakeholder communication, and project leadership.

• Mentorship from experienced AI and TechOps professionals within Novartis.

📝 Enhancement Note: The role is designed to provide hands-on experience in a rapidly evolving field within a major pharmaceutical company. It offers a unique opportunity to contribute to digital transformation and build a specialized skillset in AI-driven operational efficiency.

💡 Interview Preparation

Strategy Questions:

• "How would you approach identifying and prioritizing AI use cases within a TechOps department with limited AI expertise?"

• "Describe a time you had to explain a technical AI concept to a non-technical audience. How did you ensure they understood?"

• "Imagine a key business process is inefficient. How would you use tools like Microsoft Copilot or Power Platform to propose and implement an improvement?" Company & Culture Questions:

• "What interests you about Novartis and the pharmaceutical industry?"

• "How do you stay updated on the latest AI trends and technologies?"

• "Describe your experience working in a hybrid or remote team environment." Portfolio Presentation Strategy:

• Structure: For each project, clearly outline the problem, your proposed AI solution, the tools used (emphasizing no-code/low-code), your role, and the measurable outcomes.

• Visuals: If possible, use screenshots or brief demos to illustrate your work.

• Quantify Impact: Be ready to discuss metrics like time saved, efficiency improvements, or error reduction.

• Focus on Process: Explain your thought process, from understanding the need to implementing and refining the solution.

📝 Enhancement Note: Candidates should prepare to demonstrate not only technical proficiency but also a strong understanding of business value and a proactive, problem-solving approach. The ability to articulate complex technical concepts simply is paramount.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided Workday link, ensuring your CV is submitted in both Slovenian and English.

• Tailor your CV: Highlight your experience with AI, data science, automation, and specifically Microsoft Copilot and no-code/low-code platforms. Quantify achievements where possible.

• Prepare your portfolio: Gather examples of projects demonstrating your practical application of AI tools, focusing on problem-solving and efficiency gains.

• Research Novartis: Understand their mission, values, and the pharmaceutical industry context to articulate your interest and alignment.

• Practice interview responses: Prepare to discuss your experience with AI concepts, your approach to problem-solving, and how you would drive AI adoption in an operational setting.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions. The role is a 2-year fixed-term contract.