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 (m/d/f) / Specialist Data Science & AI (m/d/f)

Company: Novartis

Location: Mengeš, Slovenia

Job Type: Full-time (with a 2-year fixed-term contract)

Category: Data Science & Artificial Intelligence Operations

Date Posted: May 14, 2026

Experience Level: Entry to Mid-Level (1+ years)

Remote Status: Hybrid

🚀 Role Summary

• Drive the adoption and integration of Agentic and AI capabilities within local and global TechOps processes, aiming for measurable productivity and efficiency gains.

• Foster AI fluency across IT/OT and business teams, establishing communities of practice and enabling hands-on development of no-code/low-code AI solutions.

• Lead the identification and prioritization of AI use cases through bottom-up initiatives, overseeing the implementation and scaling of AI-enabled solutions.

• Facilitate the adoption of global AI platforms while advocating for site-specific requirements and enhancements to global product roadmaps.

• Establish robust governance frameworks, track benefits, and report on the impact of AI initiatives, including productivity and FTE gains, maintaining a multi-year AI development roadmap.

📝 Enhancement Note: This role is positioned as a Specialist, implying a need for practical, hands-on experience with emerging AI technologies, particularly in an enterprise context. The emphasis on "no-code/low-code" and "Agentic AI" suggests a focus on democratizing AI adoption and empowering business users to leverage AI tools without extensive programming knowledge. The fixed-term contract indicates a project-based need, likely focused on accelerating AI implementation within TechOps.

📈 Primary Responsibilities

• Spearhead the end-to-end adoption of Agentic and AI capabilities across site and global TechOps processes, embedding AI-enabled ways of working into daily operations to deliver measurable productivity gains.

• Cultivate AI fluency within IT/OT and business teams by establishing and leading Agentic/AI champion networks, facilitating 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.

• Drive the adoption of globally available Agentic & AI platforms, while continuously channeling site-specific requirements, identified gaps, and enhancement opportunities into global product backlogs for continuous improvement.

• Develop and implement clear governance structures, establish benefits tracking mechanisms, and provide comprehensive reporting on AI initiative impact, including 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 in data, platforms, integrations, and security, thereby enabling data self-service capabilities for various sites.

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

📝 Enhancement Note: The responsibilities highlight a blend of strategic oversight and tactical execution. The emphasis on "bottom-up use case identification" and "leading Agentic/AI champions" signals a proactive, empowering approach to AI adoption. The need to "continuously feed site requirements... into global product backlogs" underscores the importance of bridging local operational needs with global platform development.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a background in a quantitative field or demonstrated practical experience in Data Science, AI, or related technical disciplines is implied.

Experience: A minimum of 1 year of experience in Data Science and AI is required, with a strong emphasis on practical application and a keen interest in AI development.

Required Skills:

• At least 1 year of experience in Data Science and Artificial Intelligence.

• Strong interest and curiosity in the development of AI solutions.

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

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

• Proficiency in prompt engineering, designing workflows, and implementing basic integrations within these platforms.

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

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

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

• Ability to deeply understand business needs and translate them into effective AI solutions.

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 such as MES, ERP, and LIMS.

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

• Python programming experience.

• Practical experience with automation and robotics.

📝 Enhancement Note: The requirements emphasize practical, hands-on experience with specific AI tools like Microsoft Copilot and no-code/low-code platforms, rather than deep theoretical knowledge. The inclusion of "basic data science & analytics skills" and "SQL knowledge" indicates a need for data literacy and the ability to work with data to inform AI solutions. The "desirable requirements" suggest that prior experience in the pharmaceutical sector or with specific enterprise systems will be a significant advantage.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of no-code/low-code AI solutions developed using platforms like Microsoft Copilot Studio or Power Platform.

• Case studies showcasing the implementation of agentic solutions, highlighting prompt engineering, workflow design, and integration capabilities.

• Examples of how AI was used to automate tasks or improve efficiency in an operational setting, with quantifiable results.

• Documentation or explanations of basic data analysis performed to support AI solution development or measure its impact (e.g., KPI definitions, descriptive analysis).

Process Documentation:

• Examples of workflow designs created within no-code/low-code environments for AI-driven processes.

• Documentation of how AI solutions were integrated with existing systems or data sources.

• Metrics and reporting formats used to track the performance and benefits of implemented AI solutions, including productivity and FTE impact.

• Change management plans or strategies for introducing AI tools and fostering user adoption.

📝 Enhancement Note: For an "Entry to Mid-Level" role with a focus on "no-code/low-code," the portfolio should emphasize practical application and demonstrable results over complex, code-heavy projects. The ability to articulate the "why" and "how" of AI solutions, alongside their measurable impact, will be crucial.

💵 Compensation & Benefits

Salary Range: The salary for this Specialist role in Mengeš, Slovenia, with 1+ years of experience, is estimated to be between €30,000 and €45,000 annually. This range is based on industry benchmarks for similar roles in Slovenia, considering the required experience level and the specific skills in Data Science, AI, and no-code/low-code development. Novartis typically offers competitive compensation, and the final salary will depend on the candidate's specific qualifications and experience.

Benefits:

• Competitive salary package.

• Annual bonus.

• Flexible working schedule, tailored to individual needs.

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

• Pension scheme.

• Potential to join a collective health insurance scheme.

• Employee Recognition Scheme for achievements.

• Expanded program for promoting health in physical and mental well-being and workload management (Well-being).

• Unlimited learning and development opportunities.

Working Hours: The role is full-time, with an estimated 40 hours per week. The company offers a flexible working schedule with the possibility of adjusting hours and working from home, accommodating the hybrid work arrangement.

📝 Enhancement Note: The salary estimate is based on general market data for Slovenia for entry to mid-level technical roles. The provided benefits are comprehensive and align with typical offerings from large multinational corporations in the pharmaceutical sector. The fixed-term nature of the contract may influence some benefit eligibility, which should be clarified during the interview process.

🎯 Team & Company Context

🏢 Company Culture

Industry: Pharmaceutical and Biotechnology. Novartis is a global leader in healthcare, focused on researching, developing, manufacturing, and marketing innovative medicines. This context means operations must adhere to strict quality, regulatory, and efficiency standards.

Company Size: Novartis is a very large, multinational corporation, typically employing over 100,000 people globally. This scale implies robust infrastructure, established processes, and opportunities for cross-functional collaboration across diverse teams and regions. For operations professionals, this can mean access to significant resources and complex challenges, but also potentially more layers of bureaucracy.

Founded: Novartis was formed in 1996 through the merger of Ciba-Geigy and Sandoz, building on a long legacy of scientific innovation dating back to the mid-19th century. This history suggests a culture that values both tradition and cutting-edge advancement, with a deep commitment to long-term research and development.

Team Structure:

• The role sits within TechOps (Technology Operations), likely within a broader Digital and Technology Solutions (DDIT) or Data Science & AI (DSAI) function.

• The Specialist will collaborate with local IT/OT teams, business units, and global DDIT Ops and DSAI teams.

• A key aspect will be establishing and leading a network of "Agentic/AI champions," indicating a decentralized approach to AI adoption and skill development.

Methodology:

• Data-Driven Decision Making: Emphasis on using data to identify opportunities, measure impact, and guide AI development.

• Agile and Iterative Development: Focus on rapid deployment of no-code/low-code solutions and continuous improvement based on feedback.

• Collaboration and Knowledge Sharing: Encouraging AI fluency through communities of practice and champion networks.

• Global Alignment with Local Adaptation: Utilizing global platforms while ensuring local operational needs are met and fed back into global roadmaps.

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

📝 Enhancement Note: The company culture at Novartis is deeply rooted in science, innovation, and patient focus. For an operations role like this, it means a commitment to quality, efficiency, and the ethical application of technology. The hybrid work model and focus on well-being reflect a modern approach to employee engagement within a large, established organization.

📈 Career & Growth Analysis

Operations Career Level: This role is classified as a Specialist (Band Level 3), indicating an entry to mid-level position. It requires practical, hands-on experience and the ability to execute tasks with guidance, while also demonstrating initiative in identifying opportunities and driving adoption. The focus is on developing practical skills in AI and no-code/low-code development within an operational context.

Reporting Structure: The Specialist will likely report to a Manager or Senior Manager responsible for Digital Transformation, AI, or Technology Operations within the site or a regional TechOps division. Collaboration will be extensive with global DDIT Ops and DSAI teams, as well as local business and IT/OT stakeholders.

Operations Impact: The primary impact of this role will be on improving productivity and efficiency within TechOps processes across the Mengeš site and potentially contributing to global initiatives. By driving the adoption of Agentic and AI capabilities, the Specialist will directly influence how daily work is performed, leading to measurable gains in output and potentially cost savings through automation and optimized workflows.

Growth Opportunities:

• Specialization in AI & Automation: Deepen expertise in enterprise AI assistants, no-code/low-code platforms, and agent orchestration, becoming a go-to resource for AI solutions within TechOps.

• Cross-functional Exposure: Gain exposure to various pharmaceutical manufacturing and operational processes, understanding their unique data and AI needs.

• Project Leadership: Progress to leading larger AI implementation projects, managing stakeholders, and potentially overseeing junior team members or champions.

• Global Collaboration: Develop skills in working with global teams, contributing to international product roadmaps, and understanding diverse operational challenges.

• Transition to Senior Roles: Potential pathways to Senior Specialist, AI Lead, or Digital Transformation Manager roles within Novartis.

📝 Enhancement Note: The "Specialist" title and "1+ years experience" suggest this is an excellent stepping stone for individuals looking to build a career in applied AI and automation within a large, regulated industry. The growth path is clearly defined by increasing responsibility, scope, and specialization.

🌐 Work Environment

Office Type: The role is based in Mengeš, Slovenia, and operates under a hybrid work arrangement. This means a combination of on-site work at the Novartis facility and remote work from home. The on-site environment is expected to be modern, professional, and equipped to support pharmaceutical manufacturing operations.

Office Location(s): The primary location for this role is Mengeš, Slovenia. Novartis facilities are typically well-equipped, with access to necessary IT infrastructure and collaborative spaces. Accessibility information for Mengeš would be specific to local public transport and road networks.

Workspace Context:

• Collaborative Spaces: Access to meeting rooms, project spaces, and informal areas designed for team collaboration and brainstorming, crucial for AI use case development.

• Technology & Tools: Provision of necessary IT equipment, software licenses for AI platforms (e.g., M365 Copilot, Copilot Studio, Power Platform), and access to internal networks and data systems.

• Team Interaction: Opportunities to engage with diverse teams within TechOps, IT/OT, and business units, fostering a dynamic and knowledge-rich work environment. The role also involves building and leading a network of AI champions.

Work Schedule: The role is full-time (approx. 40 hours/week) with a flexible schedule. This flexibility, combined with the hybrid model, allows for better work-life integration, enabling operations professionals to manage their time effectively around data analysis, AI development, and team collaboration needs.

📝 Enhancement Note: The hybrid nature of the role is a significant aspect, offering a balance between in-office collaboration and remote work flexibility. For an operations role involving AI development, this balance is key for focused work and effective team engagement.

📄 Application & Portfolio Review Process

Interview Process: Novartis typically employs a multi-stage interview process designed to assess technical skills, problem-solving abilities, cultural fit, and alignment with company values.

• Initial Screening: HR or recruiter screens applications based on resume and experience.

• Hiring Manager Interview: Focus on technical skills, experience with AI tools (Copilot, Power Platform), understanding of no-code/low-code development, and motivation for the role. Expect questions about past projects and how you've applied AI.

• Technical/Case Study Interview: This may involve a practical exercise or a detailed discussion of a case study. Candidates might be asked to design a no-code/low-code AI solution for a given business problem, demonstrate prompt engineering skills, or interpret AI output. Portfolio examples will be crucial here.

• Team/Cross-functional Interview: Assessment of collaboration style, communication skills, and ability to work with diverse stakeholders (e.g., business users, IT/OT, global teams). Understanding of change management will be evaluated.

• Final Interview: May involve senior leadership to confirm cultural fit and strategic alignment.

Portfolio Review Tips:

• Showcase No-Code/Low-code Solutions: Highlight projects built with Power Platform, Copilot Studio, or similar tools. Focus on the problem solved, the process designed, and the outcome achieved.

• Demonstrate Prompt Engineering: Include examples of effective prompts and explain the rationale behind their design, showing how they elicit desired AI responses.

• Quantify Impact: Wherever possible, present metrics demonstrating productivity gains, efficiency improvements, or cost savings resulting from your AI solutions.

• Explain Your Process: Clearly articulate your approach to identifying use cases, designing workflows, integrating data, and testing solutions.

• Tailor to Novartis: If possible, frame your portfolio examples within the context of a pharmaceutical or manufacturing environment, demonstrating an understanding of industry-specific challenges.

Challenge Preparation:

• AI Use Case Brainstorming: Be prepared to brainstorm AI use cases relevant to TechOps or pharmaceutical manufacturing, focusing on opportunities for no-code/low-code solutions.

• Problem-Solving Scenarios: Practice breaking down complex business problems and proposing AI-driven solutions, detailing the steps involved in implementation.

• Communication Strategy: Prepare to explain technical concepts (like agent orchestration or prompt engineering) to a non-technical audience, emphasizing the business value.

• Data Interpretation: Be ready to discuss how you would approach data analysis to support AI initiatives, including KPI definition and interpreting AI outputs.

📝 Enhancement Note: The emphasis on "no-code/low-code" and "Agentic AI" means interviewers will likely probe for practical application and the ability to empower non-technical users. A portfolio showcasing real-world examples of these technologies in action will be highly advantageous.

🛠 Tools & Technology Stack

Primary Tools:

• Microsoft Copilot Ecosystem: M365 Copilot, Copilot Studio for building AI-powered conversational agents and workflows.

• Microsoft Power Platform: Power Apps (for building custom applications), Power Automate (for workflow automation), Power BI (for data visualization, though not explicitly listed as primary, it's a common companion).

• Agentic AI Platforms: General understanding of platforms for developing and deploying AI agents.

Analytics & Reporting:

• SQL: Basic knowledge required for data querying and interpretation.

• Data Science & Analytics Tools: Familiarity with defining KPIs, performing descriptive analysis, and interpreting AI outputs. While specific tools aren't listed, general data analysis principles are key.

• Reporting Tools: Experience in reporting productivity and FTE impact, potentially using tools like Power BI or internal reporting systems.

CRM & Automation:

• Enterprise Systems: Familiarity with consuming data from systems like MES (Manufacturing Execution Systems), ERP (Enterprise Resource Planning), and LIMS (Laboratory Information Management Systems).

• Automation & Robotics: Strong interest and potential experience with automation technologies.

📝 Enhancement Note: The technology stack is heavily geared towards the Microsoft ecosystem, particularly Copilot and Power Platform. Proficiency in these tools, combined with foundational data skills and an interest in automation, is critical for success in this role.

👥 Team Culture & Values

Operations Values:

• Innovation & Curiosity: A drive to explore and implement new AI technologies to solve business problems and enhance efficiency.

• Collaboration & Empowerment: Working together across teams, empowering colleagues through AI fluency and champion networks.

• Data-Driven Approach: Relying on data to inform decisions, measure impact, and ensure the effectiveness of AI solutions.

• Efficiency & Productivity: A continuous focus on optimizing processes and achieving measurable gains in output.

• Patient Focus: Implicitly, all operations at Novartis are geared towards ultimately supporting patient well-being by ensuring the reliable and efficient production of medicines.

Collaboration Style:

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

• Proactive Communication: Regularly sharing insights, requirements, and feedback between local sites and global platform development teams.

• Knowledge Sharing: Actively participating in or leading communities of practice for AI and Agentic technologies.

• Change Management Focus: Guiding colleagues through the adoption of new AI tools and ways of working, fostering a positive and adaptive work culture.

📝 Enhancement Note: The culture emphasizes innovation, collaboration, and a pragmatic approach to adopting new technologies like AI. The "Agentic/AI champions" model points to a culture that values distributed expertise and peer-to-peer learning within a structured corporate framework.

⚡ Challenges & Growth Opportunities

Challenges:

• Driving Adoption: Overcoming potential resistance to change and encouraging widespread adoption of AI tools among employees who may be unfamiliar or hesitant.

• Scalability of Solutions: Ensuring that no-code/low-code solutions developed can scale effectively across the site and potentially beyond, while maintaining performance and reliability.

• Data Readiness: Working with global teams to ensure data quality, accessibility, and integration necessary for robust AI applications, especially within a regulated industry.

• Balancing Global vs. Local Needs: Effectively advocating for site-specific requirements while aligning with global platform strategies and roadmaps.

• Measuring ROI: Clearly defining and tracking the productivity and FTE impact of AI initiatives to demonstrate value and secure continued investment.

Learning & Development Opportunities:

• AI Specialization: Deepen expertise in enterprise AI assistants, prompt engineering, agent orchestration, and no-code/low-code development platforms.

• Industry-Specific Insights: Gain a strong understanding of pharmaceutical manufacturing processes, regulatory requirements, and how AI can address industry-specific challenges.

• Global Collaboration Skills: Develop proficiency in working with international teams, navigating different cultural perspectives, and contributing to global digital strategies.

• Change Management Expertise: Hone skills in leading organizational change and fostering digital transformation within a large corporation.

• Access to Novartis's Learning Resources: Utilize extensive internal training programs, workshops, and potentially external certifications to enhance skills.

📝 Enhancement Note: The challenges are typical for implementing new technologies in a large, regulated environment. The growth opportunities are significant, positioning this role as a launchpad for a specialized career in applied AI within the pharmaceutical sector.

💡 Interview Preparation

Strategy Questions:

• AI Strategy: "How would you approach identifying and prioritizing AI use cases within TechOps at Novartis, focusing on no-code/low-code solutions?" (Prepare to discuss a structured approach, involving stakeholder engagement, data analysis, and ROI assessment.)

• Collaboration & Stakeholder Management: "Describe a time you had to convince a team or individual to adopt a new technology or process. How did you handle resistance?" (Focus on communication, demonstrating value, and building consensus.)

• Problem-Solving: "Imagine a common repetitive task in a manufacturing environment. How could you use AI (specifically Copilot or Power Platform) to automate or augment it?" (Be ready to outline a practical solution, including prompts, workflows, and potential data sources.)

Company & Culture Questions:

• AI Culture: "How can a company like Novartis foster AI fluency and encourage employees to embrace AI tools?" (Discuss champion networks, training programs, and creating a supportive environment.)

• Team Dynamics: "How would you collaborate with global DDIT Ops and DSAI teams to ensure data readiness for AI projects?" (Emphasize clear communication, understanding their needs, and providing site-specific insights.)

• Impact Measurement: "What key metrics would you track to demonstrate the productivity gains and FTE impact of AI initiatives in TechOps?" (Prepare to discuss specific KPIs, reporting mechanisms, and ROI calculation methods.)

Portfolio Presentation Strategy:

• Storytelling: Frame each portfolio example as a narrative: the problem, your solution (emphasizing the AI tools used), the implementation process, and the quantifiable results.

• Focus on "No-Code/Low-Code": Clearly highlight how you leveraged these platforms to achieve outcomes without extensive coding. Showcase your prompt engineering skills.

• Demonstrate Business Acumen: Connect your technical work to tangible business benefits, such as increased efficiency, reduced errors, or time savings.

• Be Ready for Q&A: Anticipate questions about your technical choices, challenges faced, and alternative approaches you considered.

📝 Enhancement Note: Candidates should be prepared to articulate their understanding of AI's practical application, especially within a regulated industry like pharmaceuticals. Demonstrating a proactive, problem-solving mindset and the ability to translate business needs into AI solutions will be key.

📌 Application Steps

To apply for this operations position:

• Submit your application through the Novartis careers portal via the provided link.

• Tailor Your CV: Ensure your resume highlights experience with Data Science, AI, Microsoft Copilot, Copilot Studio, Power Platform, and any relevant automation or robotics experience. Quantify achievements wherever possible.

• Prepare Your Portfolio: Curate examples of no-code/low-code AI solutions you’ve developed. Focus on process design, prompt engineering, and measurable impact. Be ready to walk through these during an interview.

• Research Novartis TechOps: Understand the company's focus on digital transformation and AI within its operational divisions. Familiarize yourself with their values and commitment to innovation.

• Practice Interview Questions: Prepare responses to common technical, behavioral, and situational questions, particularly those related to AI implementation, change management, and problem-solving in an operational context.

⚠️ 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.