Data Scientist
2 weeks ago
We are seeking a highly skilled Data Scientist to join our team at Lydia AI. As a Data Scientist, you will play a key role in maximizing the usability of large healthcare datasets and developing advanced machine learning models.
Responsibilities- Develop data collection plans and ensure integrity of data collected through all stages of acquisition and processing.
- Quantitatively test hypotheses about data used to create models that increase the performance of predictive models.
- Combine expert knowledge of statistical methodology and analysis with advanced programming skills to perform exploratory data analysis to uncover patterns in user's health and activities.
- Train ML models on structured, unstructured and time series data coming from electronic health record (EHR) systems, insurance claims, and wearable devices.
- Graduate degree (MS or equivalent) or higher in a quantitative field such as Mathematics, Statistics, Biostatistics, Computational biology or Medical Sciences.
- At least one (1) year of experience working with health data, such as electronic health records (EHR), lab tests, prescriptions, tabular health data, insurance claims, or risk data.
- Experience with SQL and NoSQL databases.
- Programming experience in Python; knowledge of standard data analysis tools (for example Pandas); programming experience in Typescript/Javascript or experience with other analytics software (R, SAS, STATA, MATLAB, Mathematica) is a plus.
- Familiarity with machine learning frameworks and libraries.
- General knowledge of building AI/GenAI systems.
- Familiarity with data structures, data modeling, and software architecture.
The estimated salary for this position is around $80,000-$100,000 per year, depending on experience.
About Lydia AILydai AI is an applied artificial intelligence company on a mission to protect the health and prosperity of the next billion people. We offer a digital risk scoring engine that enables businesses to enhance their customers' financial portfolios through personalized, embedded financial products.
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