Requirements
Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.2-4 years of experience as a Data Scientist or in a similar analytical role.Strong command of Python and SQL, with hands-on experience using machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.Familiarity with modern Generative AI frameworks and tools, including Hugging Face and LangChain, is highly desirable, with a Solid foundation in statistics, data analysis, and hypothesis testing, along with proficiency in Power BI for creating dashboards and reports.Experience working with cloud platforms (e.g. Azure, or GCP), strong problem-solving abilities, and the capability to communicate complex analytical insights clearly to diverse audiences.
Description
Join EVA Pharma, a leading pharmaceutical company dedicated to empowering the fight for Health and well-being as a fundamental human right. Recognized and certified as a best place to work, we are committed to fostering a supportive and innovative environment for our team members.Job Summary: We are seeking a passionate and talented Data Scientist II to join our dynamic team. The ideal candidate will contribute to our mission of enhancing human health and well-being, ensuring that we meet the highest standards of excellence in our industry.Key Responsibilities:Collect, clean, and analyze structured and unstructured datasets to uncover insights and support data-driven decisions. Build and validate predictive models and machine learning algorithms to address business and healthcare challenges.Apply cutting-edge techniques such as large language models, fine-tuning, and retrieval-augmented generation to create generative AI solutions for areas like drug discovery, clinical research, and patient engagement.Conduct statistical tests, identify key patterns and correlations, and design experiments to validate hypotheses and measure impact.Translate analytical findings into clear, actionable insights through Power BI dashboards and visual reports that inform strategic and operational decisions.Stay current with emerging AI and ML technologies, apply modern data science tools to enhance efficiency, and collaborate with data engineers to deploy and optimize production-ready models.