Основно
Data Scientist
Публикувано: 22.05.2026
Крайна дата на закриване: 06.07.2026
Препоръка за работа: a85148f7fd1f966d3e73959bde44f0f6
Информация за работата
Местоположение
galicia, Spain
Компания
JR Spain
Клиент / Работодател
Williams Lea
Препоръка за работа
a85148f7fd1f966d3e73959bde44f0f6
Тип на списък
Основно
Изисква се разрешително за работа в ЕС
Не
Публикувано
22.05.2026
Крайна дата на закриване
06.07.2026
Описание на длъжността
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
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Умения
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