QuantHealth is an AI startup supporting drug development and clinical trials. Our ground-breaking clinical trial simulator can run thousands of trials in parallel to de-risk and optimize upcoming clinical trials. Our solution, based on a huge dataset of 350M patients and 100K drugs, drastically reduces drug development costs, shortens development timelines. We are venture backed, based in Israel, and have reputable pharma customers in both Europe and the US. This is a fantastic opportunity for a data scientist who wants to join a fast-growing startup and tackle complex challenges. 

Job Overview: We are seeking a highly skilled and creative ML Engineer to join our data science team. The ideal candidate will work closely with our clinical data science team to understand delivery requirements and deliver comprehensive evaluation and improvements to our models. This role requires strong technical skills, the ability to analyze and develop new tools for evaluating and improving machine learning models, and expertise in developing ML-Ops pipelines using MLflow. 

Key Responsibilities: 

• Collaborate with the clinical data science team to gather requirements, understand needs and develop new ideas to integrate into model validation pipelines. 

• Analyze and develop new tools to evaluate machine learning models. 

• Design and implement ML-Ops pipelines using MLflow to streamline model development and deployment. 

• Develop and integrate toolkits for model selection and evaluation. 

• Create and maintain documentation for tools and workflows. 

• Develop new tools to meet specific requirements and workflows. 

• Design and implement ML systems to support clinical data science initiatives. 

• Ensure the scalability, reliability, and performance of ML systems. 

• Stay up-to-date with the latest advancements in machine learning and data science. 

Requirements: 

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field. 

• At least 4 years experience as a ML Engineer / Data Scientist. 

• Strong technical skills in Python, SQL, and Pandas. 

• Experience with version control systems such as Git. 

• Experience with MLflow and developing ML-Ops pipelines. 

• Knowledge of statistical analysis and hypothesis testing. 

• Proficiency in machine learning toolkits. 

• Strong analytical and problem-solving skills. 

• Experience with data visualization tools such as Matplotlib and Seaborn. 

• Excellent communication and collaboration skills. 

• Ability to work independently and as part of a team. 

• Creative and innovative mindset. 

Advantage: 

• Experience with Databricks and PySpark. 

• Familiarity with clinical data and healthcare industry standards is a plus. 

• Familiarity with cloud platforms such as AWS, Azure, or GCP. 

• Willingness and ability to work closely with customers to align deliveries with their needs and expectations. 

• Academic background in biology, bioinformatics, or a related clinical field.