Data Engineer (Machine Learning)

Key Skills

AWS, Flask, matplotlib, MongoDB, NoSQL, Pandas, Python Programming, SQL

Job Description

Summary: Join VideaHealth as key member of our Artificial Intelligence team on our mission to improve dental health of millions of people. You will develop data pipelines and analyze and structure large data sets using proprietary AI algorithms.

Our Mission: VideaHealth is on the mission to improve the lives of billions of people around the globe. We do this by bringing Artificial Intelligence powered solutions to the world of dentistry.

About Us:Our MIT & Harvard research has shown that dentists miss up to 50% of dental diseases, leading to delayed treatments and significant health risks. We are changing this. Spun out of MIT, we are a team of business operators, engineers, AI scientists, and clinicians bringing AI-powered software to dentists and insurances. VideaHealth’s solutions are already used by many leading Dental Chains and Insurers to improve the quality of care through better diagnoses, lower operating costs, and improved patient understanding. We are supported by some of the best investors in the world, having raised over $26M in Venture Capital from Tier 1 investors such as Spark Capital (Twitter, SnapChat, SmileDirectClub), Zetta Venture (Kaggle) and Pillar VC (PathAI), as well as angel investors such as Frederic Kerrest (Co-founder of Okta). Our work has been featured in TechCrunch, Wall Street Journal, and many other outlets. We are looking for ambitious, collaborative, self-starters to join us in making an impact on this world!

About the position: As a Data Engineer you will become a core member of Videa's Engineering team and execute on ambitious milestones, taking ownership of your own projects.

You will have a unique opportunity to be hands on and shape all stages of a complex data pipeline. This includes a large variety of tasks for which your analytical skills coupled with solid technical knowledge are a key requirement. This role will give you the opportunity to:

• Apply and develop Deep Learning algorithms in the CV/NLP space for the analysis of diverse datasets
• Consolidate, normalize and inventory large and often unstructured medical datasets
• Extract information from and add information to medical datasets that range from images to text documents
• Establish data-driven insights into patterns, correlations and opportunities based on health data
• Work with external data partners to securely and efficiently transfer datasets
• Help introduce structure to the data where appropriate

You will work closely with ML and Software engineers to analyze and structure large and diverse datasets using in-house, cutting-edge AI algorithms. We are looking for an individual with a strong analytical background who is not shy to take proactive responsibilities.

You will be able to contribute and grow your technical skills by building end to end highly impactful software medical devices that will ultimately impact the lives of millions of people. Your contributions will play a key role in building a great company from an early stage. We provide a competitive compensation package.

Requirements

• M.S. /PhD or equivalent in Math, Statistics, Computer Science, Physics or related field.
• Minimum of 2 years of hands-on experience as Data Engineer building out data pipelines for Machine Learning
• Strong software development skills including testing (Python)
• Experience with data analysis / visualization libraries (pandas, matplotlib)
• Proficiency with and experience with SQL, NoSQL (Mongo)
• Experience in data quality through integrity validation and unit testing
• Strong communication and collaboration skills
• Proactive, ambitious, and fast learner 

Preferred

• Experience with at least one deep learning framework (e.g. pytorch, keras)
• Basic knowledge of AWS
• Familiarity with medical imaging data and file formats such as DICOM
• Experience with De-identification of medical datasets
• Familiarity with building tools to interactively visualize and analyze datasets
• Experience with Flask, RestAPI, Docker