Algorithm Design and Prototyping: Design, develop, and validate predictive and analytical algorithms for CGM data. Develop robust code using advanced ML and statistical techniques to prove technical feasibility.
Feasibility and Ideation: Understand patient needs and creatively model potential algorithmic approaches using real-world sensor data.
Data Pipeline and Feature Engineering: Apply expertise in processing and managing heterogeneous time series data originating from medical devices. Execute rigorous data cleaning, imputation, transformation, and sophisticated feature engineering.
Technical Execution and Modeling: Build and optimize machine learning models (e.g., XGBoost, Neural Networks, etc.). Write high-quality, efficient, and reproducible Python code for data analysis, modeling, and experimentation.
Collaboration: Provide technical guidance within an Agile team framework to junior data science colleagues. Work effectively within a multidisciplinary, distributed team to translate project goals into actionable data science tasks.
Communication and Reporting: Synthesize complex technical results and present clear feasibility findings to diverse stakeholders.
Wymagania
Minimum of 5+ years of hands-on experience as a Data Scientist or Machine Learning Engineer.
Demonstrated experience or robust academic background (Master or PhD is highly desirable) in Data Science, Machine Learning, Statistics, or a related quantitative field.
Strong Statistical Foundation: Solid grasp of statistical principles, experimental design, and model validation techniques.
Advanced Python Proficiency: Strong proficiency in Python and its core data science ecosystem: Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, and XGBoost/LightGBM.
Time Series Data: Practical experience with the processing, analysis, and modeling of time series data from physical sensors or monitoring devices.
Additional Desirable Qualifications: Medical Domain Knowledge: Prior experience working with medical data, specifically in diabetes management (CGM/BGM), exercise physiology, or clinical nutrition data. Regulated Environment: Familiarity with the requirements and processes for software development in a regulated medical device environment. Big Data Tools: Experience with distributed computing frameworks like PySpark for handling very large datasets.
Consultant Development Program – advice on growth planning based on the latest trends and market needs in IT, including consultations with agents and growth mentors,
Relationships and access to the knowledge of the most experienced IT experts in the market – the average professional tenure of our consultants in Poland is over 10 years,
A complete benefits package, including funding for medical care, life insurance, sports cards for you and your loved ones, as well as discounts in stores in Poland and abroad.
