# Understand the field before choosing your path . Canonical HTML: https://awareness.dsti.school/ This Markdown copy is generated from the same DSTI static-site build as the canonical HTML page. It is intended for machine readability and concise retrieval. IT & Digital Jobs A practical, experience-based presentation for prospective students: how digital jobs really work, why the field remains structurally attractive, and how to enter it seriously. 45-60 minutes to understand digital careers before choosing a programme. Professional experience • Market observation • Career maps • France • Questions DSTI School of Engineering Opening perspective ## Bonjour tout le monde. I am here as an engineer first. Sébastien Corniglion ### Computer engineer, data engineering specialisation. - Former lecturer and researcher, Université Côte d'Azur. - Chief Executive Officer, Dean and co-founder of DSTI School of Engineering. - Educated at Université Côte d'Azur and The University of Edinburgh. - Computer Science & Engineering, plus Business & Management. ![Sébastien Corniglion](https://media.dsti.school/wp-content/uploads/2026/05/25131106/Sebastien-Corniglion-DSTI-School-of-Engineering.avif) Why this talk exists ### Before choosing a programme, we need to understand the field. I want students and families to understand what digital careers are, why they matter, what level of preparation they require, and how to avoid choosing a path only because a title sounds fashionable. Speaker introduction A first intuition test ## Which one is the most complex to design? This is a deliberately provocative question. The right answer is not about prestige; it is about systems, interfaces, constraints, users and failure modes. Ariane 5 ### Safety-critical engineering Extreme reliability, formal processes and physics constraints. Failure is visible, expensive and dangerous. International Space Station ### Systems integration Life support, international cooperation, maintenance, hardware, software and operations across decades. Porsche Taycan ### Physical + digital product Batteries, embedded software, safety, performance, manufacturing, regulations and user experience. Microsoft Excel ### Invisible software complexity General-purpose tools have huge compatibility, user-behaviour and edge-case complexity. Software complexity often hides in plain sight. Complexity exercise A second intuition test ## Complexity is not the same thing as luxury or price. Porsche Taycan ### High-performance complexity Advanced product engineering, battery systems, embedded intelligence, safety constraints and premium expectations. Ford Fiesta ### Mass-market complexity Reliability, cost, safety, maintainability, supply chain, manufacturing at scale and millions of real users. ### The lesson Engineering complexity is often about constraints. Digital systems are similar: the hard part is not only the algorithm, but making the system robust, usable, secure, maintainable and scalable. Complexity and constraints Market reality ## Digital jobs are not a trend. They are infrastructure. 1.3m people working in digital professions in France, average 2021-2023. 4.6% of employed workers in France are in digital professions. 55,600 projected IT professional / managerial recruitments in France in 2025, according to APEC. ### A structurally high-demand sector Globally, since its emergence, digital technology has created sustained demand for qualified professionals. AI, Data Automation and Cyber roles continue to grow - but Europe is largely a Master's-level job market for advanced roles. INSEE — French National Institute of Statistics and Economic Studies / APEC Vocabulary matters ## "Informatics" means automatic processing of information. French: informatique ### Information automatique From the beginning, computing has combined science, applied mathematics and engineering. It is not just "using computers". English terms ### Computer Science and IT Computer Science is the science of computing. Information Technology is the use of computing systems in organisations. Applied mathematics Computer science Engineering The field Two big families ## Digital work moves between reliable systems and real-world models. Engineering reliable systems ### Systems that must work - Instant secure payments across Eurozone banks. - Netflix running for millions of users at once. - Amazon protected across cloud, payments and logistics. - Google services staying available despite failures. Modelling the real world ### Models that must represent reality - Calculating a rocket path to the Moon and back. - Predicting the next video a user may watch. - Building a realistic video-game physics engine. - Processing radar, sonar or complex signals. Reliable systems / modelling First segmentation ## A simple map: what users see, and what they do not. FRONT END What I see Software interface, web application, mobile app, user interaction. FULL STACK Connecting both worlds People who understand enough of the user layer and the system layer to make coherent products. BACK END What I do not see Physical/cloud infrastructure, databases, APIs, security, AI services. Non-exhaustive: this is a first mental model, not a complete classification of all jobs. Job segmentation Another segmentation ## Digital careers cover the full life cycle of systems. It is like building a house: one person does not do everything. Different specialists work at different moments, but the final result only works if the whole system is coherent. The house analogy ### A digital product is not only "coding". Like a house, a digital system needs architecture, foundations, construction, utilities, safety checks, maintenance and coordination. Different jobs exist because the system has different kinds of complexity. This is the point of the segmentation: digital careers include analytical, technical, operational, security, infrastructure, integration and leadership profiles. Not everyone becomes the same type of developer. Career families AI careers ## Artificial Intelligence jobs are not one single job. ![Data Scientist role illustration](https://media.dsti.school/wp-content/uploads/2026/05/26170208/DataScientist-Presentation.webp) Data Scientist ### Builds and evaluates models Works with statistics, machine learning, validation, experimentation and modelling choices. ![Data Engineer role illustration](https://media.dsti.school/wp-content/uploads/2026/05/26170604/data-engineer-missions-competences-formation.webp) Data Engineer ### Makes AI work at scale Builds pipelines, platforms, storage, deployment and data infrastructure that feed AI systems. ![Data Analyst role illustration](https://media.dsti.school/wp-content/uploads/2026/05/26170728/guide-metier-inseec-hero-data-analyst.webp) Data Analyst ### Turns data into decisions Creates insight for operations, management, strategy, users and organisations. Example framing: Netflix or TikTok need all three profiles — modelling, infrastructure and decision support. AI job profiles Cyber careers ## Cybersecurity jobs are not one single job either. ![Cyber Security Engineer role illustration](https://media.dsti.school/wp-content/uploads/2026/05/26171234/gettyimages-1445359932.jpg) Security Engineer ### Designs and hardens systems Works on secure architecture, identity, access control, networks, cloud platforms, endpoints and technical protection measures. ![SOC / Incident Response Engineer role illustration](https://media.dsti.school/wp-content/uploads/2026/05/26171236/AdobeStock_432104654-scaled-1.jpeg) SOC & incident response ### Detects, investigates and responds Monitors alerts, analyses suspicious behaviour, coordinates response and helps organisations recover and learn from attacks. ![Cloud Security Engineer role illustration](https://media.dsti.school/wp-content/uploads/2026/05/26171238/What-Does-a-Cloud-Engineer-Do.jpg) Cloud & infrastructure security ### Protects the technical backbone Secures servers, networks, containers, cloud services, automation, backups and the operational environments that keep organisations running. Cybersecurity is mostly about engineering discipline: systems, networks, software, infrastructure, human behaviour, procedures, law, operations and continuous improvement. Mathematical topics exist, but most cyber careers are built on practical technical maturity. Cyber job profiles What the work actually looks like ## A day in the life of three kinds of digital specialist. No two days are identical, but each kind of role has its own rhythm. These are honest, representative days — not fixed routines — for the three broad families seen on the previous slides. **Figure:** A fitted model curve through scattered observations on a coordinate frame Science Specialist ### Turns questions into models, then tests whether they hold. - Morning Frames the question from the data and recent work — before writing any code. - Midday Prototypes a model and runs experiments against a simple baseline. - Afternoon Most attempts disappoint; works out why, adjusts the assumptions, re-runs. - End of day Writes up what was learned — often that an approach does not work yet. More of the day is reasoning, reading and checking than writing code. **Figure:** A layered system stack with a flow output, representing infrastructure and pipelines Tech Specialist ### Builds and runs the systems everything else depends on. - Morning Checks overnight pipelines, alerts and system health; fixes what broke. - Midday Designs or extends a pipeline, service or cloud component; reviews code. - Afternoon Works with others on deployment, performance and security; tests before shipping. - End of day Automates a manual step so tomorrow is a little calmer. Much of the craft is making complex systems predictable, reliable and observable. **Figure:** A bar chart with a trend line rising into a decision arrow Functional & Analytics Specialist ### Connects the technical world to real decisions. - Morning Meets the people who will use the work to pin down the real question. - Midday Pulls and checks the data; builds the analysis or dashboard. - Afternoon Translates findings for a non-technical audience; presents and discusses. - End of day Follows up on a decision the analysis helped shape. Half the job is technical; half is communication and judgement. Real roles blend all three, and the balance shifts with the team, the sector and seniority. What matters here is the rhythm of the work, not a fixed timetable. A day in the life France and digital careers ## France is a strong platform for serious digital careers. France brings together mathematical tradition, engineering culture, strategic industry and a dense technology ecosystem — exactly the kind of environment where AI, data and cybersecurity talent matters. A career platform, not only a study destination ### Digital talent matters when national systems must work. Finance, healthcare, transport, energy, defence, telecoms, luxury, mobility, public services and research all depend on robust digital systems. France digital careers Maths & engineering Strategic sectors Tech ecosystem European base #2 globally for Fields Medals in Mathematics. 55,600 IT professional / managerial recruitments in France in 2025, according to APEC. Academic rigour ### Mathematics and engineering France has a deep tradition in mathematics, scientific research and engineering education — very relevant for AI and computing. Industrial demand ### Strategic sectors Nuclear, aerospace, defence, finance, telecoms, luxury, mobility and healthcare require advanced digital systems. Technology ecosystem ### Large groups, startups and clusters France connects research institutions, international organisations, large corporations, startups and specialised technology clusters. European career logic ### Master's-level expectations Advanced digital roles in continental Europe are often built around strong academic preparation and professional maturity. Sources: Campus France / International Mathematical Union for Fields Medal context; APEC 2025 for IT professional / managerial recruitments; Insee Références 2025 for digital professions in France. France as a digital career platform Where digital careers exist ## Digital careers exist wherever systems, data and users meet. One of the strengths of this field is that it is not locked into a single industry. Digital professionals can work across almost every part of the economy. Digital skills travel across sectors Finance Healthcare Transport Energy Industry Public services Entertainment Research ### Where can you work? Finance, healthcare, transport, industry, government, education, entertainment, retail, energy and research. ### How can you work? Office-based, remote, hybrid, client-facing, behind the scenes, technical expert, project leader — many paths are possible. Bachelor level Technical, operational and junior engineering roles: building experience, discipline and practical reliability. Master's level Engineering, specialist, architecture and leadership-track roles, especially in AI, data, cyber and systems. PhD level Research, innovation and advanced scientific roles where new methods or deep expertise are central. Important reality ### The field is broad, but not vague. The more advanced the role, the more employers expect solid foundations, practical evidence and the ability to keep learning. Source context: Insee Références 2025 notes that digital professionals are present beyond digital-sector companies, which is why careers appear across finance, healthcare, transport, energy, public services, industry and research. Employment landscape Early-career salary context ## The field is attractive, but preparation still matters. Salary figures help families understand the professional logic of the field. They are a useful context, not a mechanical promise. €25,000-€28,000 Indicative early-career gross salary in France after Bachelor-level entry. €38,000-€45,000 Indicative early-career gross salary in France after Master's-level entry. How to read these numbers ### These are starting points, not ceilings. Career outcomes depend on the quality of preparation, internships, technical maturity, communication, language development, personal reliability and market timing. Skills Can the student actually build, analyse, debug and explain? Evidence Projects, internships, certifications and real work matter. Maturity Employers value reliability, curiosity and discipline. Trajectory Early salary is only one moment in a longer career path. Salary note: indicative gross annual early-career context for orientation only, not a guarantee or official benchmark; outcomes vary by region, company, language level, internships, portfolio, maturity and market cycle. Career outcomes Personal perspective ## Why I still love this field after years in it. Digital careers are attractive not only because they pay reasonably well. They are attractive because they give people options, mobility and the ability to work on real problems. Why this field remains exciting It applies everywhere Many career styles Constant evolution Real impact Long-term options It applies everywhere Every sector needs digital talent: industry, services, science, culture, healthcare, finance and public life. Many career styles Technical, analytical, managerial, research-oriented, entrepreneurial or international. It keeps evolving You never stop learning; the field rewards curiosity and disciplined adaptation. Real impact Better services, stronger security, less waste, smarter energy and more reliable organisations. Career reinvention Few fields allow so many moves between industries, technologies and responsibility levels. My advice ### Choose the field for the work, not only for the buzzwords. AI, data and cyber are powerful words. The successful students are those who accept the depth behind them. Why this field Practical advice ## How to enter digital careers seriously. 1 ### Build foundations Mathematics, logic, computing, systems, English and technical discipline. 2 ### Choose a real direction Analytics, engineering, AI, cybersecurity, software, infrastructure or systems integration. 3 ### Practise with real tools Cloud, databases, coding, pipelines, security, professional workflows and certifications. 4 ### Become employable Internships, projects, communication, reliability, maturity and the ability to learn continuously. Entering the field Closing synthesis ## The best digital careers are built on serious preparation. ### Digital jobs are everywhere. But serious roles require foundations, practice, maturity and a clear direction. ### France is a strong platform. Academic rigour, engineering culture, strategic sectors and a European career environment. ### Your pathway must be coherent. The programme, the projects, the internships and the skills must all tell the same professional story. Key takeaway Questions and next steps ## Let's discuss your digital pathway . The right question is not only "Which programme sounds good?" It is: "Which pathway fits your background, your ambitions and the level of work required to become credible in the field?" DSTI School of Engineering After this awareness discussion, continue naturally with the dedicated DSTI pages: programmes, admissions, study modes and student life. [Programmes Find the study pathway that fits your background.](https://dsti.school/programmes) [Admissions Application steps and guidance.](https://dsti.school/admissions) [Study modes On campus, Live Streamed and Online asynchronous.](https://dsti.school/study-modes) [Student life See students, campuses and the DSTI experience.](https://dsti.school/student-stories-and-videos) Thank you --- © DSTI School of Engineering 2026 - All Rights Reserved. Private Higher Education Institution - V345 - 25 July 2026