AI Data Scientist at Talan

Warsaw, Masovian Voivodeship, Poland -

Full Time

Start Date

Immediate

Expiry Date

19 Apr, 26

Salary

0.0

Posted On

20 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Data Analysis, Machine Learning, AI Solutions, LLMs, Vector Databases, Prompt Engineering, RAG Architectures, LangChain, Microsoft Azure, Google Cloud AI, Communication Skills, Cross-Functional Teams

Industry

IT Services and IT Consulting

Description

Company Description Talan – Positive Innovation Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, we are committed to delivering impactful, future-ready solutions. Talan at a Glance Headquartered in Paris and operating globally, Talan combines technology, innovation, and empowerment to deliver measurable results for our clients. Over the past 22 years, we’ve built a strong presence in the IT and consulting landscape, and we’re on track to reach €1 billion in revenue this year. Our Core Areas of Expertise Data & Technologies: We design and implement large-scale, end-to-end architecture and data solutions, including data integration, data science, visualization, Big Data, AI, and Generative AI. Cloud & Application Services: We integrate leading platforms such as SAP, Salesforce, Oracle, Microsoft, AWS, and IBM Maximo, helping clients transition to the cloud and improve operational efficiency. Management & Innovation Consulting: We lead business and digital transformation initiatives through project and change management best practices (PM, PMO, Agile, Scrum, Product Ownership), and support domains such as Supply Chain, Cybersecurity, and ESG/Low-Carbon strategies. We work with major global clients across diverse sectors, including Transport & Logistics, Financial Services, Energy & Utilities, Retail, and Media & Telecommunications. Job Description Data Analysis and Processing Collect, clean, and prepare data from various sources (SQL databases, APIs, files, cloud). Perform exploratory data analysis to identify patterns, trends, and anomalies. Optimize data storage for cost and performance efficiency. AI/ML Solution Implementation and Monitoring Build and train machine learning models to solve business problems (e.g., classification, regression, forecasting, NLP). Monitor the performance of deployed models and update them when quality drops. Create alert systems for data or model drift. Collaboration Work closely with business teams to understand their needs and translate them into analytical/technical requirements. Present analysis results and recommendations in a way that is clear for non-technical stakeholders. Visualization and Reporting Build dashboards in BI tools (e.g., Power BI, Tableau, Qlik). Create analytical reports and technical documentation. Qualifications Requirements Strong experience with Python for data analysis, machine learning, and AI solutions. Hands-on experience with LLMs, including: Vector databases Prompt engineering techniques RAG architectures Frameworks such as LangChain Experience working with cloud platforms, especially: Microsoft Azure, including Azure AI Foundry Google AI / Google Cloud AI services Strong communication skills and ability to work in cross-functional teams. High level of English and Polish is a must. Additional Information What do we offer you? Full-time contract. Smart Office Pack so that you can work comfortably from home. Training and career development. Benefits and perks such as private medical insurance, life insurance. Possibility to be part of a multicultural team and work on international projects. This is a hybrid position based in Warsaw, Poland. Possibility to manage work-permits. If you are passionate about data, development & tech, we want to meet you! Contract Type: Long term contract

Responsibilities

The AI Data Scientist will collect, clean, and prepare data, perform exploratory data analysis, and build machine learning models to solve business problems. They will also monitor model performance and collaborate with business teams to translate needs into analytical requirements.