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Our client is a leading professional services company undergoing exciting development in data science and artificial intelligence, looking for a Senior Data Scientist / AI Engineer to join their growing DATA team in Prague, Czech Republic. Skills and Requirements: BSc or MSc university degree, preferably in Mathematics, Computer Science, Physics, Operational Research or a related field. Proven track record of delivering and leading data science solutions in a commercial environment across the full data science project lifecycle. Strong command of data analysis tools and technologies, including SQL, Python, PySpark and R. Experience with large-scale data analysis technologies such as Spark, Databricks and Pig. Good knowledge of SQL and NoSQL databases, with the ability to work with modern data platforms and scalable data solutions. Knowledge of generative AI and LLM technologies, including GPT, Mistral, Llama 2 and Phi, as well as orchestrators such as LangChain and LlamaIndex. Familiarity with vector databases and storage technologies such as Chroma, Milvus and Pinecone, together with modern inference platforms. Very good command of English and strong interpersonal and communication skills, essential for working with clients and international teams. A collaborative mindset with strong teamwork and leadership skills, together with a willingness to learn new tools and software solutions. Willingness to travel as required. Role and Responsibilities: Build modern data solutions at scale – Work as part of the Prague Data Analytics team and PwC's global network of experts, designing, developing, deploying and maintaining scalable, production-grade data products. Turn data into business value – Apply quantitative business analysis, data mining and AI expertise to analyse and present data, uncovering insights and opportunities beyond the numbers. Deploy machine learning into production – Collaborate with data engineers to deploy machine learning models, including LLMs, into production environments. Use tools such as Kubeflow and MLflow to manage the end-to-end ML lifecycle and ensure seamless integration with data pipelines. Shape data-driven products – Work closely with product teams to design effective solutions to complex data problems and cooperate with Applications and Products development teams to operationalise machine learning models within final products. Contribute to global innovation – Participate in the development of PwC products and services such as the Responsible AI Platform, AI Lab, ESG suite and Media Intelligence Platform, with opportunities to contribute to solutions with global reach. Benefits: Opportunity to work on a broad variety of client projects and modern data solutions within PwC's global network. The chance to contribute to innovative products and services in data science, AI, responsible AI and ESG with global reach. Exposure to cutting-edge technologies across machine learning, generative AI, LLMs, cloud services and large-scale data platforms. Collaboration with international experts and multidisciplinary Applications, Products and Data teams. Opportunities for professional growth through continuous learning and exposure to current trends and advancements in data science. An environment where teamwork, leadership and strong client collaboration are valued. For more information – please apply for this job or send your CV directly and I will call you back to provide you with more details. Cavendish (Recruitment) Professionals Ltd are proud to be an equal opportunity employer and we believe that inclusivity begins with the candidate experience. All qualified applicants will receive consideration for employment regardless of, gender, race, age, sexual orientation, religion, or belief.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.