Data Scientist
Williams Lea Warsaw, Mazowieckie, Poland Mid
Wynagrodzenie do uzgodnienia
⚙️ Machine LearningStacjonarnieB2B CONTRACT
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O roli
Data Scientist
Data Scientist
Salary: 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: Hybrid
Williams 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 role
We 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 responsibilities Design, develop, and optimize Machine Learning and Generative AI models for enterprise applications.Perform exploratory data analysis (EDA), feature engineering, data transformation, and statistical analysis on structured and unstructured datasets.Develop 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 datasets.Knowledge 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 Scheme
You 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 careersatWL@williamslea.com(we do not accept applications to this email address).
View our Privacy Notice https://www.williamslea.com/privacy-statement
Obowiązki
Wymagania
Mile widziane
PythonMachine LearningGenerative AIScikit-learnXGBoostPyTorchTensorFlowHugging Face