Specialist za podatkovno znanost in UI (m/d/f) / Specialist Data Science & AI (m/d/f)

📍 Job Overview

Job Title: Specialist za podatkovno znanost in UI / Specialist Data Science & AI (m/d/f)

Company: Novartis

Location: Mengeš, Slovenia

Job Type: Full-time

Category: Data Science & AI / Technology Operations

Date Posted: May 14, 2026

Experience Level: 1-5 Years

Remote Status: Hybrid

🚀 Role Summary

• Drive the adoption and implementation of Agentic and AI capabilities across site and global TechOps processes, focusing on measurable productivity and efficiency gains.

• Foster AI fluency within IT/OT and business teams, acting as a key enabler for no-code/low-code AI solutions and embedding AI-driven workflows into daily operations.

• Lead the identification, prioritization, and implementation of AI use cases, ensuring scalability and sustained adoption of Agentic and AI solutions.

• Collaborate with global DDIT Ops and DSAI teams to ensure data, platform, integration, and security readiness, promoting data self-service capabilities.

• Manage change and drive cultural transformation to ensure employees embrace AI as an augmentation tool.

📝 Enhancement Note: This role is a 2-year fixed-term contract with a 6-month probation period. The focus on "Agentic and AI capabilities" and "no-code/low-code solutions" indicates a strong emphasis on practical AI application and democratization of AI tools within a large enterprise, particularly within TechOps. The requirement for AI fluency and leading champions suggests a proactive, enablement-focused approach.

📈 Primary Responsibilities

• Spearhead the end-to-end adoption of Agentic and AI capabilities within local and global processes, integrating AI-enabled ways of working into daily operations to achieve significant productivity improvements.

• Develop and enhance AI fluency across IT/OT and business teams, establishing and leading Agentic/AI champion communities to facilitate hands-on development of no-code/low-code AI solutions.

• Lead bottom-up identification of high-value use cases, collaborate with site leadership for prioritization, and oversee the successful delivery, scaling, and sustained adoption of Agentic and AI solutions.

• Advocate for and drive the adoption of globally available Agentic and AI platforms, while actively channeling site-specific requirements, gaps, and enhancement opportunities back into global product roadmaps.

• Establish clear governance frameworks, meticulously track benefits (including productivity and FTE impact), and maintain a forward-looking, multi-year Agentic & AI roadmap.

• Partner closely with Global DDIT Ops and DSAI teams to ensure robust data, platform, integration, and security readiness, and to empower sites with effective data self-service capabilities.

• Lead comprehensive change management initiatives and cultural transformation efforts to ensure employees readily embrace AI as an augmentation tool and actively leverage Agentic & AI solutions in their daily work.

📝 Enhancement Note: The responsibilities highlight a blend of strategic oversight (roadmap, governance, change management) and hands-on enablement (AI fluency, champion communities, no-code/low-code development). The emphasis on "bottom-up use case identification" suggests an expectation for proactive problem-solving and initiative from the candidate.

🎓 Skills & Qualifications

Education: While specific degree requirements are not stated, a background in a quantitative field such as Computer Science, Data Science, Engineering, or a related discipline is implied by the nature of the role.

Experience: Minimum of 1 year of experience in Data Science and AI, with a strong interest and curiosity for AI development. This role is designated as a 2-year fixed-term contract.

Required Skills:

• Demonstrated hands-on experience with enterprise AI assistants, with a strong preference for Microsoft Copilot (M365 Copilot, Copilot Studio).

• Proven ability to develop agentic solutions using no-code/low-code platforms such as Power Platform and Copilot Studio, encompassing prompt engineering, workflow design, and basic integrations.

• Practical understanding of agent orchestration, identification of reusable patterns, and the process of scaling AI agents within operational environments.

• Basic data science and analytics skills, including defining Key Performance Indicators (KPIs), performing descriptive analysis, proficiency in SQL, and the ability to interpret AI outputs.

• Strong interest and curiosity in automation and robotics.

Preferred Skills:

• Knowledge of pharmaceutical processes and the pharmaceutical industry.

• Experience with data fundamentals, including the ability to consume, combine, and interpret data from enterprise systems (e.g., MES, ERP, LIMS), along with a basic understanding of data quality, access, and governance principles.

• Experience with Python programming.

• Hands-on experience with automation and robotics technologies.

📝 Enhancement Note: The "1+ years experience" combined with the focus on practical application of tools like Microsoft Copilot and Power Platform suggests this role is suitable for early-career professionals or those looking to transition into AI enablement within a corporate setting. The "Desirable requirements" indicate a preference for candidates with industry-specific knowledge and broader technical skills.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of successful AI solutions developed using no-code/low-code platforms (e.g., Power Platform, Copilot Studio), highlighting practical application and problem-solving.

• Case studies showcasing the ability to identify business needs and translate them into functional AI or agentic solutions.

• Examples of workflow design and basic integration implementation within AI applications.

Process Documentation:

• Ability to document AI solution designs, including workflows, integrations, and prompt logic, ensuring clarity for both technical and non-technical stakeholders.

• Documentation of change management processes related to AI tool adoption, including training materials and user guides.

• Records of benefits tracking and reporting for implemented AI solutions, demonstrating measurable productivity and efficiency gains.

📝 Enhancement Note: While a formal portfolio isn't explicitly requested, demonstrating practical experience through a resume or during interviews with examples of no-code/low-code AI solutions, prompt engineering, and workflow automation will be critical. The emphasis is on tangible results and practical application rather than theoretical concepts.

💵 Compensation & Benefits

Salary Range: While a specific salary range is not provided, for a Specialist Data Science & AI role with 1-5 years of experience in Mengeš, Slovenia, the estimated annual gross salary range would typically fall between €35,000 and €55,000. This estimate is based on industry benchmarks for similar roles in the Slovenian market, considering the company's size (Novartis is a large multinational) and the specialized nature of AI and Data Science skills.

Benefits:

• Competitive salary package.

• Annual bonus.

• Flexible working schedule, tailored to individual needs.

• Possibility of working from home (Hybrid work arrangement).

• Pension scheme.

• Opportunity to join a collective health insurance scheme.

• Employee Recognition Scheme to acknowledge achievements.

• Expanded program for the promotion of health, focusing on physical and mental well-being and workload management ("Full of Life" program).

• Unlimited learning and development opportunities, including access to training and educational resources.

Working Hours: The standard working hours are approximately 40 hours per week, with a flexible schedule allowing for tailored adjustments and the option to work from home, reflecting a hybrid work model.

📝 Enhancement Note: The provided benefits are comprehensive and align with those offered by large multinational corporations. The salary estimate is based on general market data for Slovenia and the specified role and experience level. Actual compensation will depend on the candidate's specific qualifications and experience.

🎯 Team & Company Context

🏢 Company Culture

Industry: Pharmaceutical and Biotechnology. Novartis is a global leader in healthcare, focused on discovering, developing, manufacturing, and marketing prescription medicines. This context means operations roles often involve high stakes, stringent quality controls, and a focus on patient well-being.

Company Size: Novartis is a large multinational corporation, employing over 100,000 people globally. This scale implies robust processes, extensive resources, and opportunities for global collaboration and impact.

Founded: 1996, through the merger of Ciba-Geigy and Sandoz. This history suggests a foundation built on innovation and a long-standing commitment to scientific advancement.

Team Structure:

• The role operates within the TechOps (Technology Operations) function, likely part of a broader Digital and Information Technology (DDIT) organization.

• It involves close collaboration with global DDIT Ops and Data Science & AI (DSAI) teams, as well as local IT/OT and business unit teams.

• The Specialist will act as an AI champion and enabler, suggesting a decentralized approach to AI adoption where champions facilitate adoption within their respective business units.

Methodology:

• Data-Driven Decision Making: Emphasis on using data science, AI, and analytics to inform decisions and drive improvements.

• Agile & Iterative Development: The focus on "no-code/low-code" and "bottom-up use case identification" suggests agile methodologies for rapid development and iteration of AI solutions.

• Process Optimization: A core objective is to leverage AI to achieve measurable productivity and efficiency gains in TechOps processes.

• Global Standardization & Local Adaptation: Balancing the adoption of global AI platforms with the need to incorporate site-specific requirements and feedback.

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

📝 Enhancement Note: The pharmaceutical industry context is crucial; it implies a highly regulated environment where AI solutions must be robust, secure, and compliant. The "TechOps" focus means AI applications will likely be geared towards manufacturing, supply chain, R&D support, or operational efficiency within these domains.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a Specialist, indicating an individual contributor role with a focus on executing specific AI and data science initiatives within TechOps. It requires practical skills and hands-on experience rather than extensive management responsibilities, though leadership in AI enablement is expected.

Reporting Structure: The Specialist will report into a local TechOps or IT leadership structure, with strong collaborative ties to global DDIT Ops and DSAI teams. This dual reporting/collaboration model requires strong communication and stakeholder management skills.

Operations Impact: The role is designed to have a direct impact on operational efficiency and productivity by embedding AI capabilities into daily processes. Success will be measured by tangible improvements in productivity, FTE savings, and the successful adoption of AI tools across the site.

Growth Opportunities:

• AI Specialization: Deepen expertise in specific AI tools and platforms (e.g., Microsoft Copilot suite, Power Platform) and emerging AI technologies.

• Cross-functional Leadership: Develop leadership skills by acting as an AI champion, training colleagues, and influencing adoption across different departments.

• Process Improvement Expertise: Gain in-depth knowledge of pharmaceutical TechOps processes and how AI can be applied to optimize them.

• Project Management: Opportunities to lead AI implementation projects from ideation to sustained adoption, managing scope, resources, and timelines.

• Transition to Global Roles: Potential to contribute to global AI strategy, product roadmaps, and best practices based on site-specific learnings.

📝 Enhancement Note: The "Specialist" title and the emphasis on hands-on development and enablement suggest this role is ideal for someone looking to build practical AI application skills within a large enterprise. The fixed-term nature (2 years) could also serve as an opportunity to gain specific project experience and then transition into other roles within Novartis or the broader industry.

🌐 Work Environment

Office Type: The role is designated as "Hybrid," indicating a blend of on-site work at the Mengeš facility and remote work flexibility. This allows for a balance between in-person collaboration and focused individual work.

Office Location(s): Mengeš, Slovenia. This is the primary work location, and candidates must be able to access it, as no relocation support is provided.

Workspace Context:

• Collaborative Environment: The hybrid model and emphasis on AI champions and cross-functional partnerships suggest a culture that values collaboration, knowledge sharing, and team-based problem-solving.

• Technology-Rich: As a specialist in Data Science & AI, the workspace will be equipped with the necessary technology and access to platforms like Microsoft Copilot, Power Platform, and relevant data systems.

• Innovation Hub: Being at the forefront of AI adoption in TechOps, the environment is likely dynamic and encourages experimentation with new AI tools and methodologies.

Work Schedule: Approximately 40 hours per week, with a flexible schedule that allows for adjustments to accommodate personal needs and project demands, supporting the hybrid work arrangement.

📝 Enhancement Note: The "Hybrid" designation is key. While remote work is an option, the "site and global Processes" responsibility implies regular on-site presence will be necessary for collaboration, hands-on development, and engaging with local teams and leadership.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of CVs, likely focusing on AI experience, no-code/low-code proficiency, and relevant technical skills. Candidates are expected to submit CVs in both Slovenian and English.

• Technical/Skills Assessment: Interviews may include discussions on specific AI concepts, tool usage (e.g., Copilot, Power Platform), prompt engineering techniques, and problem-solving scenarios. A practical assessment or case study related to AI application in TechOps is possible.

• Behavioral & Cultural Fit: Assessment of communication skills, proactivity, curiosity, and ability to drive change and collaborate within a hybrid, global-to-local team structure.

• Final Interview: Likely with hiring managers and key stakeholders to discuss the role's strategic impact, career growth, and final alignment.

Portfolio Review Tips:

• Showcase Practical Application: Prepare examples of AI solutions you've built using no-code/low-code tools. Focus on the problem addressed, the solution implemented, and the measurable outcomes achieved (e.g., time saved, efficiency gained).

• Highlight Copilot/Power Platform Experience: If you have direct experience with Microsoft Copilot (M365 Copilot, Copilot Studio) or Power Platform, be ready to discuss specific projects, features used, and challenges overcome.

• Prompt Engineering Examples: Be prepared to discuss your approach to prompt engineering, including examples of prompts you've designed and how they were refined for better results.

• Data Understanding: Demonstrate your ability to interpret AI outputs and how you would connect AI solutions to relevant data sources (MES, ERP, LIMS), even with basic data governance knowledge.

• Concise Case Studies: Structure your examples as mini case studies: Problem -> Solution -> Result. Quantify impact wherever possible.

Challenge Preparation:

• AI Use Case Identification: Be ready to brainstorm potential AI use cases within a pharmaceutical TechOps context (e.g., automating report generation, improving data entry, streamlining process documentation, predictive maintenance insights).

• No-Code/Low-Code Solution Design: You might be asked to outline a basic workflow or prompt for a given scenario using a no-code/low-code approach.

• Change Management Scenarios: Consider how you would encourage adoption of new AI tools among colleagues who may be resistant or unfamiliar with AI.

📝 Enhancement Note: The dual-language CV requirement is important. Candidates should ensure their CVs are polished in both Slovenian and English. The emphasis on "hands-on" and "practical" skills suggests interviewers will probe deeply into actual project experience rather than theoretical knowledge.

🛠 Tools & Technology Stack

Primary Tools:

• Microsoft Copilot Suite: M365 Copilot for general productivity augmentation, Copilot Studio for building custom AI conversational agents and workflows.

• No-code/Low-code Platforms: Primarily Microsoft Power Platform (Power Apps, Power Automate, Power BI) for building custom applications, automating workflows, and creating data visualizations.

• Agent Orchestration Tools: Implied by "agent orchestration" and "scaling agents," this could refer to features within Copilot Studio or other enterprise AI platforms that manage AI agent interactions.

Analytics & Reporting:

• SQL: Essential for basic data querying and understanding data sources.

• Power BI: Likely used for creating dashboards and reports to track AI solution performance and benefits.

• Data Interpretation: Ability to interpret AI outputs and descriptive analytics.

CRM & Automation:

• Power Automate: For designing and implementing automated workflows.

• Enterprise Systems Integration: Experience with integrating AI solutions with enterprise systems like MES (Manufacturing Execution System), ERP (Enterprise Resource Planning), and LIMS (Laboratory Information Management System) is desirable.

📝 Enhancement Note: The technology stack is heavily centered around the Microsoft ecosystem for AI and low-code development. Proficiency in these tools, particularly Copilot Studio and Power Platform, will be a significant advantage. Understanding how these tools integrate with existing enterprise systems is also key.

👥 Team Culture & Values

Operations Values:

• Innovation & Curiosity: A drive to explore and adopt new AI technologies and experiment with AI-driven solutions.

• Collaboration & Empowerment: Fostering a team environment where colleagues are empowered with AI tools and knowledge, and where cross-functional collaboration is key.

• Efficiency & Productivity: A strong focus on leveraging AI to deliver measurable improvements in operational efficiency and productivity.

• Data-Driven Approach: Utilizing data and AI insights to inform decisions, optimize processes, and demonstrate value.

• Patient Focus: While this role is in TechOps, the overarching company mission to help patients means that operational improvements ultimately support the delivery of life-changing medicines.

Collaboration Style:

• Cross-functional Integration: Working closely with IT/OT, business units, and global DSAI/DDIT Ops teams to ensure AI solutions meet diverse needs and integrate seamlessly.

• Champion Network: Actively engaging with and supporting a network of AI champions across different departments to drive adoption and gather feedback.

• Knowledge Sharing: A culture that encourages sharing best practices, learnings, and solutions related to AI implementation and usage.

• Proactive Communication: Maintaining open and regular communication with stakeholders at local and global levels to manage expectations, report progress, and address challenges.

📝 Enhancement Note: The company's commitment to diversity and inclusion, as well as its mission to help patients, likely permeates the team culture. The role requires someone who can not only implement technology but also champion its adoption and integrate it into the existing operational fabric.

⚡ Challenges & Growth Opportunities

Challenges:

• Driving AI Adoption: Overcoming potential resistance to AI, ensuring AI fluency, and encouraging active use of new tools among employees with varying technical backgrounds.

• Scalability & Governance: Ensuring AI solutions are scalable, maintainable, and adhere to appropriate governance and security standards within a large enterprise.

• Data Readiness: Addressing potential gaps in data quality, access, and integration required for effective AI implementation across different systems.

• Measuring Impact: Clearly defining and tracking productivity and FTE impact metrics for AI solutions to demonstrate ROI and justify further investment.

• Rapidly Evolving AI Landscape: Staying current with the fast-paced advancements in AI technology and adapting solutions accordingly.

Learning & Development Opportunities:

• Specialized AI Training: Access to advanced training on Microsoft Copilot, Power Platform, and other AI/automation tools.

• Industry Exposure: Gaining deep insights into pharmaceutical TechOps processes and unique industry challenges.

• Cross-Functional Project Experience: Working on diverse AI projects impacting various operational areas within Novartis.

• Mentorship: Opportunities to learn from experienced data scientists, AI specialists, and IT leaders within Novartis.

• Certification Pathways: Potential to pursue certifications in Microsoft AI and low-code development platforms.

📝 Enhancement Note: The challenges are typical for roles focused on AI adoption and change management. The growth opportunities are significant, especially for someone looking to specialize in enterprise AI enablement within a regulated industry.

💡 Interview Preparation

Strategy Questions:

• "How would you approach identifying and prioritizing AI use cases within a pharmaceutical manufacturing environment to drive productivity gains?" (Focus on structured methodology, stakeholder engagement, and impact assessment.)

• "Describe your experience building a no-code/low-code AI solution. What was the problem, what tools did you use, and what was the outcome?" (Highlight practical, hands-on experience, tool proficiency, and results.)

• "How would you foster AI fluency and encourage adoption of new AI tools among colleagues who may be hesitant or unfamiliar with AI?" (Focus on communication, training, support, and change management strategies.)

Company & Culture Questions:

• "What interests you most about Novartis and this specific role within TechOps?" (Show genuine interest in the company's mission and the role's contribution to operational efficiency.)

• "How do you stay updated with the rapidly evolving field of AI and automation?" (Demonstrate continuous learning and curiosity.)

Portfolio Presentation Strategy:

• Focus on Impact: For each project example, clearly articulate the business problem, the AI solution implemented (especially no-code/low-code aspects), and the quantifiable results (e.g., time saved, efficiency improved, errors reduced).

• Tool Demonstration: Be prepared to briefly walk through a demo or screenshots of a solution, highlighting key features like workflows, prompts, or integrations.

• Storytelling: Frame your experience as a narrative – the challenge, your approach, the solution, and the lessons learned.

• Relevance: Tailor your examples to showcase skills most relevant to the job description, such as AI assistant usage, prompt engineering, and automation within an operational context.

📝 Enhancement Note: The interview preparation emphasizes practical application, problem-solving, and communication. Candidates should be ready to articulate their AI knowledge in a business context and demonstrate how they can translate technical capabilities into tangible business value.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided link on the Novartis careers portal. Ensure your CV is prepared and submitted in both Slovenian and English languages.

• Customize Your CV: Tailor your resume to highlight specific experience with AI assistants (especially Microsoft Copilot), no-code/low-code platforms (Power Platform, Copilot Studio), SQL, and any relevant automation or data science projects. Quantify achievements wherever possible.

• Prepare Your Portfolio Examples: Gather specific examples or case studies of AI solutions you have developed or contributed to. Focus on demonstrating your practical skills in prompt engineering, workflow design, and achieving measurable efficiency gains.

• Research Novartis TechOps: Understand Novartis's business, its commitment to innovation, and the potential applications of AI within the pharmaceutical industry. Familiarize yourself with their "Full of Life" well-being program and diversity initiatives.

• Practice Interview Questions: Rehearse answers to common behavioral and technical questions, focusing on how your skills and experience align with the role's requirements, particularly in driving AI adoption and improving operational efficiency.

⚠️ 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.