Senior Data Scientist

About the role:

Hello Heart is looking for a Senior Data Scientist to join our expanding data group. As a part of our Data Science group, you will work on highly complicated challenges, from research to production. You'll research, design, implement and optimize ML models that drive our core recommendations and personalization systems. Your work will directly contribute to improving healthcare practices and enhancing the well-being of individuals.

Your responsibilities:

• You’ll take ownership of recommendation and personalization modeling projects, including design, model training, architecture, performance evaluation, and ongoing monitoring.
• You’ll research and experiment with machine learning, deep learning, optimization, and statistics algorithms to solve a wide range of real-life problems that can actually improve people’s lives.
• You will explore and improve the machine learning infrastructure to meet the criteria of scalability, reliability, performance, and efficiency  of the models.
• You’ll work closely with the product and translate user behaviors into personalized digital insights that will be used on a daily basis across the world.
• You’ll innovate and make new ideas happen fast, in an agile way. Yes, even in the data group.

Your Skills:

• 2+ years of hands-on experience in industry settings developing recommendation systems
• 4+ years of hands-on experience in developing machine learning models using Python.
• 4+ years of hands-on industry experience in implementing machine learning models in production 
• BSc in an appropriate technology field (Computer Science, Statistics, Applied Math, Neuroscience, Physics, Econometrics).
• Strong software development skills and experience writing production quality code for large scale machine learning in real-world scenarios.
• Experience with data cleaning, preprocessing, and feature engineering techniques. 
• Strong mathematical skills with knowledge of statistical methods
• Expertise in AI algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines.
• Expertise in Causal Inference And Reinforcement Learning - advantage
• MSc, or PhD in an appropriate technology field or equivalent experience - advantage.
• Experience with standard analytics tools and deep learning frameworks such as scikit-learn, PyTorch / TensorFlow - advantage.,
• Knowledge of containerization technologies (e.g., Docker) and cloud platforms (e.g., AWS, Azure, or GCP) - advantage.,