Osnovno

Data Scientist

galicia, Spain Podjetje: JR Spain Naročnik / delodajalec: Williams Lea
Objavljeno: 22.05.2026
Datum zaprtja: 06.07.2026
Referenčna delovna mesta: a85148f7fd1f966d3e73959bde44f0f6

Informacije o delovnih mestih

Lokacija
galicia, Spain
Podjetje
JR Spain
Naročnik / delodajalec
Williams Lea
Referenčna delovna mesta
a85148f7fd1f966d3e73959bde44f0f6
Vrsta seznama
Osnovno
Zahtevano delovno dovoljenje EU
Ne
Objavljeno
22.05.2026
Datum zaprtja
06.07.2026

Opis delovnega mesta

Data ScientistSalary: 200,000 PCN per annum, plus company benefitsLocation: Warsaw, PolandContract: Full TimeShifts: 40 hours per week, Monday – Friday, 8.30am until 5:30pm with 1 hours unpaid lunch breakWork model: HybridWilliams Lea seeks a Mid Level Data Scientist to join our team!Williams Lea is the leading global provider of tech-enabled business and marketing services helping clients manage and transform processes through resilient, scalable 24/7 operations. We combine deep expertise, agentic AI-imbedded workflows, and a global delivery model into a tech-enabled, seamless human expert-in-the-loop experience that helps clients achieve superior business outcomes.Built on a strong heritage and great client relationships, we harness deep industry expertise, emerging technology and our global “Optishore” delivery model to plan, build, execute and measure business processes, driving operational agility and digital transformation at speed and scale.Williams Lea, an RRD company, serves clients in 20 countries across four continents and has 15,000 employees worldwide.Purpose of roleWe are seeking an experienced Mid-Level Data Scientist with a minimum of 4 years of experience in Machine Learning, Artificial Intelligence, and advanced analytics to develop scalable AI-driven solutions for enterprise and client-facing applications. The role involves working on predictive modelling, Generative AI use cases, data analysis, feature engineering, experimentation, and AI systems across cloud environments. The ideal candidate should possess strong expertise in statistical modelling, Machine Learning algorithms, Python programming, cloud platforms, and data-driven problem-solving, with the ability to collaborate across business and technical teams.The recruitment process will involve an initial 45 minutes MS teams interview to understand suitable skills and experience, successful applicant will be invited to a 45 minutes technical assessment which will involve a deployment/coding followed by panel questions and answers.Key responsibilitiesDesign, develop, and optimize Machine Learning and Generative AI models for enterprise exploratory data analysis (EDA), feature engineering, data transformation, and statistical analysis on structured and unstructured predictive models, classification models, regression models, NLP solutions, and AI-driven workflows.Work on LLM integrations, prompt engineering, RAG pipelines, and AI powered automation solutions.Build and evaluate ML models using Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, or Hugging Face frameworks.Analyze model performance using appropriate evaluation metrics and continuously improve model accuracy and stability.Collaborate with ML Engineers, Platform Teams, Product Owners, Solution Architects, and Business StakeholdersSupport production deployment activities, model validation, monitoring, and troubleshooting.Work with cloud platforms including AWS and/or Azure for AI/ML workloads.Personal attributesBachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.Minimum 4 years of experience in Data Science, Machine Learning, or AI related roles.Strong proficiency in Python programming and data science libraries such as Pandas, NumPy, and Scikit-learn.Strong understanding of Machine Learning algorithms, statistics, probability, and data modeling techniques.Experience in NLP, Generative AI, LLMs, or advanced analytics solutions.Hands-on experience with cloud platforms such as AWS and/or Azure.Experience with SageMaker, Bedrock, Azure ML, or equivalent AI/ML platforms is preferred.Understanding of ML lifecycle, experimentation, model evaluation, and production monitoring.Experience working with SQL, APIs, and large-scale of MLOps, CI/CD, Docker, or cloud deployment workflows is an advantage.Strong analytical thinking, communication, and stakeholder management skills.Using AI in your applicationWe’re happy for you to use AI tools to research us, polish your cv/cover letter, and practice interviews. Please make sure everything you submit reflects your authentic skills and experience.To keep things fair, please don’t use AI to invent or exaggerate achievements, complete assessments (unless we say it’s allowed), or to generate live interview answers.Rewards and BenefitsWe believe in supporting our employees in both their professional and personal lives. As part of our commitment to your well-being, we offer a comprehensive benefits package, including but not limited to:26 days holiday, plus bank holidaysPrivate medical insuranceStatutory contributions which include; pension, disability insurance, sickness insurance and accident insuranceReferral SchemeYou will also have the opportunity to work for a global employer who is dedicated to offering each and every employee an enjoyable, challenging and rewarding career with future career development prospects!Equality and DiversityThe Company values the differences that a diverse workforce brings to the organisation and will not discriminate because of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race (which includes colour, nationality and ethnic or national origins), religion or belief, sex or sexual orientation (each of these being a “protected characteristic” in discrimination law). It will not discriminate because of any other irrelevant factor and will build a culture that values openness, fairness and transparency.If you have a disability and would prefer to apply in a different format or would like to make a reasonable adjustment to enable you to make an interview please contact us at (we do not accept applications to this email address).View our Privacy Notice https://www.williamslea.com/privacy-statement #J-18808-Ljbffr

Spretnosti

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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