Autonomous Healthcare
About Autonomous Healthcare
At Autonomous Healthcare, we are at the forefront of medical innovation, developing the next generation of devices that will revolutionize patient care. Our mission is to commercialize breakthrough medical technologies by leveraging cutting-edge AI and autonomous systems. We believe that the best solutions are built together, and we are looking for a key member to join our collaborative R&D team.
Job Summary We are seeking a versatile and dynamic Data Scientist to fill a unique, multi-faceted role on our team. This position goes beyond traditional analytics, blending three critical functions: generating strategic insights, detecting anomalies, and modeling future-state scenarios. You will be empowered to analyze complex clinical and pharmacy data from different angles—acting as an investigator to uncover suspicious patterns, a strategist to answer key analytics questions, and a futurist to simulate the impact of potential changes. The ideal candidate is a skilled technical practitioner who thrives on variety and is passionate about using a full spectrum of data science techniques to improve outcomes.
Analytics & Insight Generation
Perform comprehensive exploratory data analysis (EDA) on healthcare datasets to answer critical questions about trends.
Design and execute complex SQL queries to extract, aggregate, and prepare data for analysis.
Translate analytical findings into compelling narratives, visualizations, and actionable recommendations.
Anomaly & Fraud Detection
Design, build, and deploy machine learning models (both unsupervised and supervised) to identify suspicious or anomalous patterns.
Investigate flagged activities by digging deep into the data, documenting findings, and providing evidence-based context for review.
Simulation & Predictive Analysis
Develop and run discrete event simulations to model clinical pathways, and clinic/pharmacy workflows.
Use simulation-based analysis to conduct “what-if” scenarios.
Analyze and interpret simulation outputs to forecast outcomes and provide data-driven recommendations.
Required Skills & Qualifications
Proven experience in a data science role that demonstrates analytical versatility across different types of projects.
Strong proficiency in Python and its core data science libraries, including
Pandas ,
NumPy , and
Scikit-learn .
Hands‑on experience with a range of
machine learning
techniques, including both unsupervised (e.g., clustering, isolation forests) and supervised (e.g., classification) methods.
Expertise in writing and optimizing complex SQL queries.
Extensive experience using
Jupyter Notebooks
for iterative analysis, model development, and reporting.
Solid foundation in applied statistics (e.g., hypothesis testing, regression, probability).
Excellent problem‑solving skills, with the ability to toggle between investigative analysis, exploratory research, and predictive modeling.
Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Operations Research, or a related discipline.
Preferred Qualifications (A Plus)
Direct experience with
discrete event simulation
and familiarity with simulation frameworks.
Experience deploying machine learning models into production environments.
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Job Summary We are seeking a versatile and dynamic Data Scientist to fill a unique, multi-faceted role on our team. This position goes beyond traditional analytics, blending three critical functions: generating strategic insights, detecting anomalies, and modeling future-state scenarios. You will be empowered to analyze complex clinical and pharmacy data from different angles—acting as an investigator to uncover suspicious patterns, a strategist to answer key analytics questions, and a futurist to simulate the impact of potential changes. The ideal candidate is a skilled technical practitioner who thrives on variety and is passionate about using a full spectrum of data science techniques to improve outcomes.
Analytics & Insight Generation
Perform comprehensive exploratory data analysis (EDA) on healthcare datasets to answer critical questions about trends.
Design and execute complex SQL queries to extract, aggregate, and prepare data for analysis.
Translate analytical findings into compelling narratives, visualizations, and actionable recommendations.
Anomaly & Fraud Detection
Design, build, and deploy machine learning models (both unsupervised and supervised) to identify suspicious or anomalous patterns.
Investigate flagged activities by digging deep into the data, documenting findings, and providing evidence-based context for review.
Simulation & Predictive Analysis
Develop and run discrete event simulations to model clinical pathways, and clinic/pharmacy workflows.
Use simulation-based analysis to conduct “what-if” scenarios.
Analyze and interpret simulation outputs to forecast outcomes and provide data-driven recommendations.
Required Skills & Qualifications
Proven experience in a data science role that demonstrates analytical versatility across different types of projects.
Strong proficiency in Python and its core data science libraries, including
Pandas ,
NumPy , and
Scikit-learn .
Hands‑on experience with a range of
machine learning
techniques, including both unsupervised (e.g., clustering, isolation forests) and supervised (e.g., classification) methods.
Expertise in writing and optimizing complex SQL queries.
Extensive experience using
Jupyter Notebooks
for iterative analysis, model development, and reporting.
Solid foundation in applied statistics (e.g., hypothesis testing, regression, probability).
Excellent problem‑solving skills, with the ability to toggle between investigative analysis, exploratory research, and predictive modeling.
Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Operations Research, or a related discipline.
Preferred Qualifications (A Plus)
Direct experience with
discrete event simulation
and familiarity with simulation frameworks.
Experience deploying machine learning models into production environments.
#J-18808-Ljbffr