Lead Data Scientist

Tel Aviv-Yafo, Tel Aviv District, Israel.

R&D Full time

Description

It's 2023, and we believe that health benefits should be as simple as breathing. Welcome to Healthee - your digital compass to navigate the vast world of healthcare benefits. Imagine discovering your coverage, identifying the right provider, understanding your costs, and booking an appointment—all in the time it takes to send a tweet! That's what we do, and we do it in 27 seconds flat.

Our quest is to redefine healthcare experiences for employees worldwide through our cutting-edge AI platform, ensuring they not only navigate but truly optimize their health plans.

Are you driven by a mission to make a difference? Dive in!

Lead Data Scientist Opportunity

If you love discovering hidden insights, are curious about how AI can help humans, and can lead a team to innovate, then we're looking for you.

Step into a role where you shape the future of AI at Healthee. As the lead data scientist, you won't just be handling data; you'll guide how we make our AI smarter and better using your creativity, innovation and experience. At Healthee, we're not just looking for someone who knows data; we want someone who sees its potential in machine learning, NLU and different algorithms. Join Healthee, and help us make our AI the best in the health world.

Responsibilities

• Strategic Product Thinking: Work closely with product managers, engineering teams and other stakeholders to grasp requirements and chart out the data science roadmap.
• Algorithmic Leadership: Design and refine machine learning models and NLU features. Lead the evolution of our AI-driven product by leveraging both existing and new data insights.
• Data Technology Decisions: Evaluate and select the best data science techniques, tools, and frameworks that suit the product's needs. Stay on top of the latest in AI, machine learning, and NLU trends.
• Model Quality & Standards: Uphold superior standards in model development and deployment. Champion innovative approaches, ensuring our algorithms remain cutting-edge yet reliable.
• Performance Optimization: Supervise and guide on improving model performance, efficiency, and ensuring smooth integration into Healthee’s products.
• Technical Documentation: Drive the development of clear and detailed documents explaining our AI methodologies, model decisions, and data science processes.
• Prototyping, Execution & Testing (Hands On): Lead initiatives to test new data-driven ideas, machine learning models, and NLU techniques, assessing their fit and potential for our product, being able to run, execute and test different ideas using scripts.
• Adaptability: Showcase a strong ability to thrive in a dynamic setting, pivoting with the ever-evolving landscape of data science and AI in healthcare.
  
  

• Extensive Experience: 7+ years in data science roles, with a proven track record of leading significant projects or teams.
• Algorithmic Mastery: Deep understanding of machine learning algorithms, NLU processes, and AI-driven product development.
• Programming Proficiency: Solid experience in Python or similar data science languages. Familiarity with libraries and frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Database Excellence: Hands-on experience with a range of database technologies, including but not limited to SQL, NoSQL, Vectors DB, and graph databases. Understanding of distributed databases like DynamoDB or Redshift is a plus.
• MLOps Solutions Experience: Proven expertise in deploying ML models into production, optimizing performance, and ensuring scalability. Experience in orchestrating end-to-end data science pipelines, from data acquisition and annotation to preparation, modeling, evaluation, and deployment.
• Cloud Competence: Strong knowledge and hands-on experience with major cloud platforms like AWS, Google Cloud, or Azure. Familiarity with AI and ML services on these platforms is beneficial.
• Continuous Model Monitoring: Experience with tools and strategies for tracking model performance, continuous integration, and iterative enhancement post-deployment.
• Data Security: Advanced understanding of data security protocols, privacy standards, and best practices, especially within the healthcare domain.
• Collaboration & Communication: Outstanding communication abilities, able to explain complex data concepts to varied audiences. Proven skills in guiding and collaborating with interdisciplinary teams.
• Eagerness to Learn: A passion for staying updated with the newest trends in data science, AI, and related fields, with an inclination to integrate new discoveries into workflows.
• Problem-solving Ability: A keen analytical mindset, passionate about solving complex data challenges, and driving teams to innovate and refine solutions.