Data Scientist ML Consultant

Algolytics develops the Scoring.One platform and solutions in the areas of AutoML, MLOps, Feature Store, real-time decisioning, credit risk, antifraud, and customer intelligence. We are looking for someone who wants to combine data science work with real-world model deployment in production environments and influence the development of our products. This is a role for someone who enjoys not only building models but also understanding business problems, working with clients, designing analytical processes, and bringing solutions to practical application. What you will be doing: * Building and prototyping predictive models for clients in the financial, telecommunications, e-commerce, retail, and services sectors. * Creating solutions in the areas of credit risk, antifraud, customer intelligence, churn, response modeling, recommendations, behavioral segmentation, and transactional data analysis. * Preparing data for modeling: data analysis, feature engineering, data quality validation, building training and test sets. * Deploying models and decision logic in production environments using the Scoring.one platform. * Participating in R&D projects related to AutoML, MLOps, Feature Store, real-time scoring, LLM/NLP, and automation of analytical processes. * Collaborating with business clients: analyzing needs, translating business problems into analytical solutions, presenting results and recommendations. * Collaborating with the development team on the development of our analytical product functionalities. * Testing, validating, and monitoring the quality of models and decision rules. * Preparing dedicated procedures, components, and functional extensions for the Algolytics platform. We are looking for someone who has: * Minimum 5 years of experience in Data Science, Machine Learning, data modeling, or analytical projects. * Very good knowledge of Python and SQL. * Good fundamentals in statistics, machine learning, data mining, and model validation. * Experience in consulting projects, implementation projects, or projects carried out for business clients. * Ability to independently analyze a business problem and propose an analytical approach. * Experience in preparing data for ML, feature engineering, and model testing. * Ability to communicate with the business and collaborate with the development team. * Knowledge of English sufficient for working with documentation and project communication. * Completed higher education, preferably in fields such as: Computer Science, Mathematics, Quantitative Methods, Econometrics, Statistics, Computational Physics, or related. An additional advantage will be: * Experience in credit risk modeling, scoring, fraud detection, or the FinTech sector. * Knowledge of MLOps, Feature Store, AutoML, MLflow, Databricks, Snowflake, Azure ML, AWS SageMaker, or similar solutions. * Experience with very large datasets. * Knowledge of SAS, R, SPSS/IBM Modeler, KNIME, RapidMiner, Statistica, or other analytical tools. * Knowledge of Java/Groovy or experience in creating production components. * Experience with REST API, SOAP, system integrations, or deploying models as services. * Knowledge of NLP, LLM, generative AI, image analysis, or data from sensors/IoT. * Willingness to share knowledge: presentations at conferences, webinars, training, industry publications, or academic activity. What we offer: * Work on models and decision systems that are actively used in production by enterprise clients. * Opportunity to combine Data Science, MLOps, AutoML, credit risk, antifraud, and real-time decisioning. * Significant influence on the development of the proprietary Scoring.One platform and Algolytics products. * Ambitious projects for large organizations in the financial, telecommunications, e-commerce, retail, and services industries. * High degree of independence and the opportunity to propose your own analytical and product solutions. * Work in an experienced, small team where the impact of your work is easily visible. * Attractive salary and bonuses twice a year. * Private medical care. * Office in the center of Warsaw. * Flexible cooperation model: UoP (Employment Contract) or B2B.