Requirements: English
Company: Philip Morris Polska Distribution Splka z o.o.
Region: Krakw , Lesser Poland Voivodeship
MAKE HISTORY WITH US!
At PMI, weve chosen to do something incredible. Were totally transforming our business, and building our future on smoke-free products with the power to improve the lives of a billion smokers worldwide.
With huge change, comes huge opportunity. So, wherever you join us, youll enjoy the freedom to dream up and deliver better, brighter solutions and the space to move your career forward in endlessly different directions.
ROLE OVERVIEW:
As a Machine Learning Engineer, you will apply advanced data science techniques to analyze data and ML models, assessing and fine-tuning them for optimal business and technical performance. This role requires deep understanding of ML frameworks and techniques, including data exploration and manipulation. You will be working with both structured and unstructured data, utilizing specialized programming languages and tools to drive effective decision-making and create business value.
WHAT WE OFFER YOU?
- Private medical and dental care, life insurance;
- Hybrid work opportunity and flexible working arrangements;
- Employee pension plan;
- Multisport program;
- Holiday, cultural Christmas bonus;
- Wide range of trainings, optional language classes, further education and professional qualification support possibility;
- Free bike and car parking for all employees.
- Masters degree in: Data Science, Computer Science, Statistics or a related field.
- 3 + years of experience in data science or related role.
- Proficient in at least one of the following languages: Python, R, SAS or Julia.
- Strong knowledge of machine learning algorithms, techniques and libraries (eg. TensorFlow, PyTorch)
- Experience with data pre-processing, feature engineering and model evaluation
- Experience working with Snowflake, Docker, Kubernetes, AWS: S3, EMR and SageMaker is a great plus
- Experience with Atlassian Suite (Bitbucket/JIRA/Confluence)
- Proven understanding and addressing ethical implications and biases in models, analytical and critical thinking
- Problem-solving and innovative thinking to develop new models and approaches.
- Experience working directly with remote technical teams.
MAKE HISTORY WITH US!
At PMI, weve chosen to do something incredible. Were totally transforming our business, and building our future on smoke-free products with the power to improve the lives of a billion smokers worldwide.
With huge change, comes huge opportunity. So, wherever you join us, youll enjoy the freedom to dream up and deliver better, brighter solutions and the space to move your career forward in endlessly different directions.
ROLE OVERVIEW:
As a Machine Learning Engineer, you will apply advanced data science techniques to analyze data and ML models, assessing and fine-tuning them for optimal business and technical performance. This role requires deep understanding of ML frameworks and techniques, including data exploration and manipulation. You will be working with both structured and unstructured data, utilizing specialized programming languages and tools to drive effective decision-making and create business value.
WHAT WE OFFER YOU?
- Private medical and dental care, life insurance;
- Hybrid work opportunity and flexible working arrangements;
- Employee pension plan;
- Multisport program;
- Holiday, cultural Christmas bonus;
- Wide range of trainings, optional language classes, further education and professional qualification support possibility;
- Free bike and car parking for all employees.
,[Lead end-to-end analytics projects - from gathering business requirements and validating hypotheses to delivering outputs, visualizing data, and generating actionable insights that drive value. , Develop, train, and deploy machine learning models assessing them for performance, robustness and bias. , Choose appropriate metrics to evaluate outcomes. , Identify and resolve issues both before and after model deployment. , Anticipate and address ethical, bias, privacy, and data protection implications of ML/AI models. Establish traceability for outcomes produced by ML models. , Maintain thorough documentation of data science processes, models, and experiments to ensure reproducibility and knowledge sharing. , Provide data-driven insights and recommendations to support strategic business decisions and initiatives while also identifying opportunities for process optimization and automation, striving for continuous improvement in data management practices. , Actively anticipate and reso